Schizophrenia (SZ) is a complex disorder characterized by a range of behavioral and cognitive symptoms as well as structural and functional alterations in multiple cortical and subcortical structures. SZ is associated with reduced functional network connectivity involving core regions such as the anterior cingulate cortex (ACC) and the thalamus. However, little is known whether effective coupling, the directed influence of one structure over the other, is altered during rest in the ACC–thalamus network.

We collected resting-state fMRI and diffusion-weighted MRI data from 18 patients and 20 healthy controls. We analyzed fronto-thalamic effective connectivity using dynamic causal modeling for cross-spectral densities in a network consisting of the ACC and the left and right medio-dorsal thalamic regions. We studied structural connectivity using fractional anisotropy (FA).

We found decreased coupling strength from the right thalamus to the ACC and from the right thalamus to the left thalamus, as well as increased inhibitory intrinsic connectivity in the right thalamus in patients relative to controls. ACC-to-left thalamus coupling strength correlated with the Positive and Negative Syndrome Scale (PANSS) total positive syndrome score and with delusion score. Whole-brain structural analysis revealed several tracts with reduced FA in patients, with a maximum decrease in white matter tracts containing fronto-thalamic and cingulo-thalamic fibers.

We found altered effective and structural connectivity within the ACC–thalamus network in SZ. Our results indicate that ACC–thalamus network activity at rest is characterized by reduced thalamus-to-ACC coupling. We suggest that positive symptoms may arise as a consequence of compensatory measures to imbalanced fronto-thalamic coupling.

Only 30% or fewer of individuals at clinical high risk (CHR) convert to full psychosis within 2 years. Efforts are thus underway to refine risk identification strategies to increase their predictive power. Our objective was to develop and validate the predictive accuracy and individualized risk components of a mobile app-based psychosis risk calculator (RC) in a CHR sample from the SHARP (ShangHai At Risk for Psychosis) program.

In total, 400 CHR individuals were identified by the Chinese version of the Structured Interview for Prodromal Syndromes. In the first phase of 300 CHR individuals, 196 subjects (65.3%) who completed neurocognitive assessments and had at least a 2-year follow-up assessment were included in the construction of an RC for psychosis. In the second phase of the SHARP sample of 100 subjects, 93 with data integrity were included to validate the performance of the SHARP-RC.

The SHARP-RC showed good discrimination of subsequent transition to psychosis with an AUC of 0.78 (p < 0.001). The individualized risk generated by the SHARP-RC provided a solid estimation of conversion in the independent validation sample, with an AUC of 0.80 (p = 0.003). A risk estimate of 20% or higher had excellent sensitivity (84%) and moderate specificity (63%) for the prediction of psychosis. The relative contribution of individual risk components can be simultaneously generated. The mobile app-based SHARP-RC was developed as a convenient tool for individualized psychosis risk appraisal.

The SHARP-RC provides a practical tool not only for assessing the probability that an individual at CHR will develop full psychosis, but also personal risk components that might be targeted in early intervention.

Disruptions in neural circuits underlying emotion regulation (ER) may be a mechanism linking child maltreatment with psychopathology. We examined the associations of maltreatment with neural responses during passive viewing of negative emotional stimuli and attempts to modulate emotional responses. We investigated whether the influence of maltreatment on neural activation during ER differed across development and whether alterations in brain function mediated the association between maltreatment and a latent general psychopathology (‘p’) factor.

Youth aged 8–16 years with (n = 79) and without (n = 72) exposure to maltreatment completed an ER task assessing neural responses during passive viewing of negative and neutral images and effortful attempts to regulate emotional responses to negative stimuli. P-factor scores were defined by a bi-factor model encompassing internalizing and externalizing psychopathology.

Maltreated youth had greater activation in left amygdala and salience processing regions and reduced activation in multiple regions involved in cognitive control (bilateral superior frontal gyrus, middle frontal gyrus, and dorsal anterior cingulate cortex) when viewing negative v. neutral images than youth without maltreatment exposure. Reduced neural recruitment in cognitive control regions mediated the association of maltreatment with p-factor in whole-brain analysis. Maltreated youth exhibited increasing recruitment with age in ventrolateral prefrontal cortex during reappraisal while control participants exhibited decreasing recruitment with age. Findings were similar after adjusting for co-occurring neglect.

Child maltreatment influences the development of regions associated with salience processing and cognitive control during ER in ways that contribute to psychopathology.

Loneliness is a growing public health issue in the developed world. Among older adults, loneliness is a particular challenge, as the older segment of the population is growing and loneliness is comorbid with many mental as well as physical health issues. Comorbidity and common cause factors make identifying the antecedents of loneliness difficult, however, contemporary machine learning techniques are positioned to tackle this problem.

This study analyzed four cohorts of older individuals, split into two age groups – 45–69 and 70–79 – to examine which common psychological and sociodemographic are associated with loneliness at different ages. Gradient boosted modeling, a machine learning technique, and regression models were used to identify and replicate associations with loneliness.

In all cohorts, higher emotional stability was associated with lower loneliness. In the older group, social circumstances such as living alone were also associated with higher loneliness. In the younger group, extraversion's association with lower loneliness was the only other confirmed relationship.

Different individual and social factors might underlie loneliness differences in distinct age groups. Machine learning methods have the potential to unveil novel associations between psychological and social variables, particularly interactions, and mental health outcomes.

Psychotherapies for depression are equally effective on average, but individual responses vary widely. Outcomes can be improved by optimizing treatment selection using multivariate prediction models. A promising approach is the Personalized Advantage Index (PAI) that predicts the optimal treatment for a given individual and the magnitude of the advantage. The current study aimed to extend the PAI to long-term depression outcomes after acute-phase psychotherapy.

Data come from a randomized trial comparing cognitive therapy (CT, n = 76) and interpersonal psychotherapy (IPT, n = 75) for major depressive disorder (MDD). Primary outcome was depression severity, as assessed by the BDI-II, during 17-month follow-up. First, predictors and moderators were selected from 38 pre-treatment variables using a two-step machine learning approach. Second, predictors and moderators were combined into a final model, from which PAI predictions were computed with cross-validation. Long-term PAI predictions were then compared to actual follow-up outcomes and post-treatment PAI predictions.

One predictor (parental alcohol abuse) and two moderators (recent life events; childhood maltreatment) were identified. Individuals assigned to their PAI-indicated treatment had lower follow-up depression severity compared to those assigned to their PAI-non-indicated treatment. This difference was significant in two subsets of the overall sample: those whose PAI score was in the upper 60%, and those whose PAI indicated CT, irrespective of magnitude. Long-term predictions did not overlap substantially with predictions for acute benefit.

If replicated, long-term PAI predictions could enhance precision medicine by selecting the optimal treatment for a given depressed individual over the long term.

Recent work suggests that antihypertensive medications may be useful as repurposed treatments for mood disorders. Using large-scale linked healthcare data we investigated whether certain classes of antihypertensive, such as angiotensin antagonists (AAs) and calcium channel blockers, were associated with reduced risk of new-onset major depressive disorder (MDD) or bipolar disorder (BD).

Two cohorts of patients treated with antihypertensives were identified from Scottish prescribing (2009–2016) and hospital admission (1981–2016) records. Eligibility for cohort membership was determined by a receipt of a minimum of four prescriptions for antihypertensives within a 12-month window. One treatment cohort (n = 538 730) included patients with no previous history of mood disorder, whereas the other (n = 262 278) included those who did. Both cohorts were matched by age, sex and area deprivation to untreated comparators. Associations between antihypertensive treatment and new-onset MDD or bipolar episodes were investigated using Cox regression.

For patients without a history of mood disorder, antihypertensives were associated with increased risk of new-onset MDD. For AA monotherapy, the hazard ratio (HR) for new-onset MDD was 1.17 (95% CI 1.04–1.31). Beta blockers' association was stronger (HR 2.68; 95% CI 2.45–2.92), possibly indicating pre-existing anxiety. Some classes of antihypertensive were associated with protection against BD, particularly AAs (HR 0.46; 95% CI 0.30–0.70). For patients with a past history of mood disorders, all classes of antihypertensives were associated with increased risk of future episodes of MDD.

There was no evidence that antihypertensive medications prevented new episodes of MDD but AAs may represent a novel treatment avenue for BD.

We examined demographic, clinical, and psychological characteristics of a large cohort (n = 368) of adults with dissociative seizures (DS) recruited to the CODES randomised controlled trial (RCT) and explored differences associated with age at onset of DS, gender, and DS semiology.

Prior to randomisation within the CODES RCT, we collected demographic and clinical data on 368 participants. We assessed psychiatric comorbidity using the Mini-International Neuropsychiatric Interview (M.I.N.I.) and a screening measure of personality disorder and measured anxiety, depression, psychological distress, somatic symptom burden, emotional expression, functional impact of DS, avoidance behaviour, and quality of life. We undertook comparisons based on reported age at DS onset (<40 v. ⩾40), gender (male v. female), and DS semiology (predominantly hyperkinetic v. hypokinetic).

Our cohort was predominantly female (72%) and characterised by high levels of socio-economic deprivation. Two-thirds had predominantly hyperkinetic DS. Of the total, 69% had ⩾1 comorbid M.I.N.I. diagnosis (median number = 2), with agoraphobia being the most common concurrent diagnosis. Clinical levels of distress were reported by 86% and characteristics associated with maladaptive personality traits by 60%. Moderate-to-severe functional impairment, high levels of somatic symptoms, and impaired quality of life were also reported. Women had a younger age at DS onset than men.

Our study highlights the burden of psychopathology and socio-economic deprivation in a large, heterogeneous cohort of patients with DS. The lack of clear differences based on gender, DS semiology and age at onset suggests these factors do not add substantially to the heterogeneity of the cohort.

Sleep disturbance has been consistently identified as an independent contributor to suicide risk. Inflammation has emerged as a potential mechanism linked to both sleep disturbance and suicide risk. This study tested associations between sleep duration, insomnia, and inflammation on suicidal ideation (SI) and history of a suicide attempt (SA).

Participants included 2329 adults with current or remitted depression and/or anxiety enrolled in the Netherlands Study of Depression and Anxiety. Sleep duration, insomnia, past week SI, and SA were assessed with self-report measures. Plasma levels of C-reactive protein, interleukin-6, and tumor necrosis factor-α were obtained.

Short sleep duration (⩽6 h) compared to normal sleep duration (7–9 h) was associated with reporting a prior SA, adjusting for covariates [adjusted odds ratio (AOR) 1.68, 95% CI 1.13–2.51]. A higher likelihood of SI during the past week was observed for participants with long sleep duration (⩾10 h) compared to normal sleep duration (AOR 2.22, 95% CI 1.02–4.82), more insomnia symptoms (AOR 1.44, 95% CI 1.14–1.83), and higher IL-6 (AOR 1.31, 95% CI 1.02–1.68). Mediation analyses indicated that the association between long sleep duration and SI was partially explained by IL-6 (AOR 1.02, 95% CI 1.00–1.05).

These findings from a large sample of adults with depression and/or anxiety provide evidence that both short and long sleep duration, insomnia symptoms, and IL-6 are associated with the indicators of suicide risk. Furthermore, the association between long sleep duration and SI may operate through IL-6.

The prevalence and impact of motor coordination difficulties in children with copy number variants associated with neurodevelopmental disorders (ND-CNVs) remains unknown. This study aims to advance understanding of motor coordination difficulties in children with ND-CNVs and establish relationships between intelligence quotient (IQ) and psychopathology.

169 children with an ND-CNV (67% male, median age = 8.88 years, range 6.02–14.81) and 72 closest-in-age unaffected siblings (controls; 55% male, median age = 10.41 years, s.d. = 3.04, range 5.89–14.75) were assessed with the Developmental Coordination Disorder Questionnaire, alongside psychiatric interviews and standardised assessments of IQ.

The children with ND-CNVs had poorer coordination ability (b = 28.98, p < 0.001) and 91% of children with an ND-CNV screened positive for suspected developmental coordination disorder, compared to 19% of controls (OR = 42.53, p < 0.001). There was no difference in coordination ability between ND-CNV genotypes (F = 1.47, p = 0.184). Poorer coordination in children with ND-CNV was associated with more attention deficit hyperactivity disorder (ADHD) (β = −0.18, p = 0.021) and autism spectrum disorder trait (β = −0.46, p < 0.001) symptoms, along with lower full-scale (ß = 0.21, p = 0.011), performance (β = −0.20, p = 0.015) and verbal IQ (β = 0.17, p = 0.036). Mediation analysis indicated that coordination ability was a full mediator of anxiety symptoms (69% mediated, p = 0.012), and a partial mediator of ADHD (51%, p = 0.001) and autism spectrum disorder trait symptoms (66%, p < 0.001) as well as full scale IQ (40%, p = 0.002), performance IQ (40%, p = 0.005) and verbal IQ (38%, p = 0.006) scores.

The findings indicate that poor motor coordination is highly prevalent and closely linked to risk of mental health disorder and lower intellectual function in children with ND-CNVs. Future research should explore whether early interventions for poor coordination ability could ameliorate neurodevelopmental risk.

The brain functional correlates of autobiographical recall are well established, but have been little studied in schizophrenia. Additionally, autobiographical memory is one of a small number of cognitive tasks that activates rather than de-activates the default mode network, which has been found to be dysfunctional in this disorder.

Twenty-seven schizophrenic patients and 30 healthy controls underwent functional magnetic resonance imaging while viewing cue words that evoked autobiographical memories. Control conditions included both non-memory-evoking cues and a low level baseline (cross fixation).

Compared to both non-memory evoking cues and low level baseline, autobiographical recall was associated with activation in default mode network regions in the controls including the medial frontal cortex, the posterior cingulate cortex and the hippocampus, as well as other areas. Clusters of de-activation were seen outside the default mode network. There were no activation differences between the schizophrenic patients and the controls, but the patients showed clusters of failure of de-activation in non-default mode network regions.

According to this study, patients with schizophrenia show intact activation of the default mode network and other regions associated with recall of autobiographical memories. The finding of failure of de-activation outside the network suggests that schizophrenia may be associated with a general difficulty in de-activation rather than dysfunction of the default mode network per se.

One hypothesis proposed to underlie formal thought disorder (FTD), the incoherent speech is seen in some patients with schizophrenia, is that it reflects impairment in frontal/executive function. While this proposal has received support in neuropsychological studies, it has been relatively little tested using functional imaging. This study aimed to examine brain activations associated with FTD, and its two main factor-analytically derived subsyndromes, during the performance of a working memory task.

Seventy patients with schizophrenia showing a full range of FTD scores and 70 matched healthy controls underwent fMRI during the performance of the 2-back version of the n-back task. Whole-brain corrected, voxel-based correlations with FTD scores were examined in the patient group.

During 2-back performance the patients showed clusters of significant inverse correlation with FTD scores in the inferior frontal cortex and dorsolateral prefrontal cortex bilaterally, the left temporal cortex and subcortically in the basal ganglia and thalamus. Further analysis revealed that these correlations reflected an association only with ‘alogia’ (poverty of speech, poverty of content of speech and perseveration) and not with the ‘fluent disorganization’ component of FTD.

This study provides functional imaging support for the view that FTD in schizophrenia may involve impaired executive/frontal function. However, the relationship appears to be exclusively with alogia and not with the variables contributing to fluent disorganization.

Neurophysiological patterns may distinguish which youth are at risk for the well-documented increase in internalizing symptoms during adolescence. Adolescents with internalizing problems exhibit altered resting-state functional connectivity (RSFC) of brain regions involved in socio-affective processing. Whether connectivity-based biotypes differentiate adolescents’ levels of internalizing problems remains unknown.

Sixty-eight adolescents (37 females) reported on their internalizing problems at ages 14, 16, and 18 years. A resting-state functional neuroimaging scan was collected at age 16. Time-series data of 15 internalizing-relevant brain regions were entered into the Subgroup-Group Iterative Multi-Model Estimation program to identify subgroups based on RSFC maps. Associations between internalizing problems and connectivity-based biotypes were tested with regression analyses.

Two connectivity-based biotypes were found: a Diffusely-connected biotype (N = 46), with long-range fronto-parietal paths, and a Hyper-connected biotype (N = 22), with paths between subcortical and medial frontal areas (e.g. affective and default-mode network regions). Higher levels of past (age 14) internalizing problems predicted a greater likelihood of belonging to the Hyper-connected biotype at age 16. The Hyper-connected biotype showed higher levels of concurrent problems (age 16) and future (age 18) internalizing problems.

Differential patterns of RSFC among socio-affective brain regions were predicted by earlier internalizing problems and predicted future internalizing problems in adolescence. Measuring connectivity-based biotypes in adolescence may offer insight into which youth face an elevated risk for internalizing disorders during this critical developmental period.

Aberrant salience may contribute to the development of schizophrenia symptoms via alterations in reward processing and motivation. However, tests of this hypothesis have yielded inconsistent results. These inconsistencies may reflect problems with the validity and specificity of measures of aberrant salience in schizophrenia. Therefore, we investigated relationships among measures of aberrant salience, reward, and motivation in schizophrenia and anxiety.

Individuals with schizophrenia (n = 30), anxiety (n = 33) or unaffected by mental disorder (n = 30) completed measures of aberrant salience [Aberrant Salience Inventory (ASI), Salience Attribution Test (SAT)], motivation (Effort Expenditure for Reward Task), and reinforcer sensitivity (Stimulus Chase Task).

Schizophrenia participants scored higher than anxiety (d = 0.71) and unaffected (d = 1.54) groups on the ASI and exhibited greater aberrant salience (d = 0.60) and lower adaptive salience (d = 0.98) than anxious participants on the SAT. There was no evidence of a correlation between measures of aberrant salience. Schizophrenia was associated with related deficits in motivated behaviour and maladaptive reward processing. However, these differences in reward processing did not correlate with aberrant salience measures.

The results suggest that key measures of aberrant salience have limited specificity and validity. These problems may account for inconsistent findings reported in the literature.

Certain migrant groups are at an increased risk of psychotic disorders compared to the native-born population; however, research to date has mainly been conducted in Europe. Less is known about whether migrants to other countries, with different histories and patterns of migration, such as Australia, are at an increased risk for developing a psychotic disorder. We tested this for first-generation migrants in Melbourne, Victoria.

This study included all young people aged 15–24 years, residing in a geographically-defined catchment area of north western Melbourne who presented with a first episode of psychosis (FEP) to the Early Psychosis Prevention and Intervention Centre (EPPIC) between 1 January 2011 and 31 December 2016. Data pertaining to the at-risk population were obtained from the Australian 2011 Census and incidence rate ratios were calculated and adjusted for age, sex and social deprivation.

In total, 1220 young people presented with an FEP during the 6-year study period, of whom 24.5% were first-generation migrants. We found an increased risk for developing psychotic disorder in migrants from the following regions: Central and West Africa (adjusted incidence rate ratio [aIRR] = 3.53, 95% CI 1.58–7.92), Southern and Eastern Africa (aIRR = 3.06, 95% CI 1.99–4.70) and North Africa (aIRR = 5.03, 95% CI 3.26–7.76). Migrants from maritime South East Asia (aIRR = 0.39, 95% CI 0.23–0.65), China (aIRR = 0.25, 95% CI 0.13–0.48) and Southern Asia (aIRR = 0.44, 95% CI 0.26–0.76) had a decreased risk for developing a psychotic disorder.

This clear health inequality needs to be addressed by sufficient funding and accessible mental health services for more vulnerable groups. Further research is needed to determine why migrants have an increased risk for developing psychotic disorders.

Among Veterans, post-traumatic stress disorder (PTSD) has been shown to be associated with obesity and accelerated weight gain. Less is known among the general population. We sought to determine the impact of PTSD on body mass index (BMI) and weight change among individuals with exposure to the World Trade Center (WTC) disaster.

We examined individuals from the WTC Health Registry. PTSD symptoms were assessed on multiple surveys (Waves 1–4) using the PTSD Checklist-Specific. Three categories of post-9/11 PTSD were derived: no, intermittent, and persistent. We examined two outcomes: (1) Wave 3 BMI (normal, overweight, and obese) and (2) weight change between Waves 3 and 4. We used multivariable logistic regression to assess the association between PTSD and BMI (N = 34 958) and generalized estimating equations to assess the impact of PTSD on weight change (N = 26 532). Sex- and age-stratified analyses were adjusted for a priori confounders.

At Wave 3, the observed prevalence of obesity was highest among the persistent (39.5%) and intermittent PTSD (36.6%) groups, compared to the no PTSD group (29.3%). In adjusted models, persistent and intermittent PTSD were consistently associated with a higher odds of obesity. Weight gain was similar across all groups, but those with persistent and intermittent PTSD had higher estimated group-specific mean weights across time.

Our findings that those with a history of PTSD post-9/11 were more likely to have obesity is consistent with existing literature. These findings reaffirm the need for an interdisciplinary focus on physical and mental health to improve health outcomes.

There is increasing interest in the clinical and aetiological overlap between autism spectrum disorders and schizophrenia spectrum disorders, reported to co-occur at both diagnostic and trait levels. Individually, sub-clinical autistic and psychotic traits are associated with poor clinical outcomes, including increased depressive symptomatology, self-harming behaviour and suicidality. However, the implications when both traits co-occur remain poorly understood. The study aimed to (1) examine the relationship between autistic and psychotic traits and (2) determine if their co-occurrence increases depressive symptomatology, self-harm and suicidality.

Cross-sectional data from a self-selecting (online and poster advertising) sample of the adult UK population (n = 653) were collected using an online survey. Validated self-report measures were used to assess sub-clinical autistic and psychotic traits, depressive symptomatology, self-harming behaviour and suicidality. Correlation and regression analyses were performed.

A positive correlation between sub-clinical autistic and positive psychotic traits was confirmed (rs = 0.509, p < 0.001). Overall, autistic traits and psychotic traits were, independently, significant predictors of depression, self-harm and suicidality. Intriguingly, however, depression was associated with a negative interaction between the autistic domain attention to detail and psychotic traits.

This study supports previous findings that sub-clinical autistic and psychotic traits are largely independently associated with depression, self-harm and suicidality, and is novel in finding that their combined presence has no additional effect on depression, self-harm or suicidality. These findings highlight the importance of considering both autistic and psychotic traits and their symptom domains in research and when developing population-based depression prevention and intervention strategies.

In the past decade, network analysis (NA) has been applied to psychopathology to quantify complex symptom relationships. This statistical technique has demonstrated much promise, as it provides researchers the ability to identify relationships across many symptoms in one model and can identify central symptoms that may predict important clinical outcomes. However, network models are highly influenced by node selection, which could limit the generalizability of findings. The current study (N = 6850) tests a comprehensive, cognitive–behavioral model of eating-disorder symptoms using items from two, widely used measures (Eating Disorder Examination Questionnaire and Eating Pathology Symptoms Inventory).

We used NA to identify central symptoms and compared networks across the duration of illness (DOI), as chronicity is one of the only known predictors of poor outcome in eating disorders (EDs).

Our results suggest that eating when not hungry and feeling fat were the most central symptoms across groups. There were no significant differences in network structure across DOI, meaning the connections between symptoms remained relatively consistent. However, differences emerged in central symptoms, such that cognitive symptoms related to overvaluation of weight/shape were central in individuals with shorter DOI, and behavioral central symptoms emerged more in medium and long DOI.

Our results have important implications for the treatment of individuals with enduring EDs, as they may have a different core, maintaining symptoms. Additionally, our findings highlight the importance of using comprehensive, theoretically- or empirically-derived models for NA.

Attention-deficit hyperactivity disorder (ADHD) is associated with later depression and there is considerable genetic overlap between them. This study investigated if ADHD and ADHD genetic liability are causally related to depression using two different methods.

First, a longitudinal population cohort design was used to assess the association between childhood ADHD (age 7 years) and recurrent depression in young-adulthood (age 18–25 years) in N = 8310 individuals in the Avon Longitudinal Study of Parents and Children (ALSPAC). Second, two-sample Mendelian randomization (MR) analyses examined relationships between genetic liability for ADHD and depression utilising published Genome-Wide Association Study (GWAS) data.

Childhood ADHD was associated with an increased risk of recurrent depression in young-adulthood (OR 1.35, 95% CI 1.05–1.73). MR analyses suggested a causal effect of ADHD genetic liability on major depression (OR 1.21, 95% CI 1.12–1.31). MR findings using a broader definition of depression differed, showing a weak influence on depression (OR 1.07, 95% CI 1.02–1.13).

Our findings suggest that ADHD increases the risk of depression later in life and are consistent with a causal effect of ADHD genetic liability on subsequent major depression. However, findings were different for more broadly defined depression.