Research on the Alternative DSM-5 Model for Personality Disorders (AMPD) in DSM-5's Section-III has demonstrated acceptable interrater reliability, a largely consistent latent structure, substantial correlations with theoretically and clinically relevant measures, and evidence for incremental concurrent and predictive validity after controlling for DSM-5's Section II categorical personality disorders (PDs). However, the AMPD is not yet widely used clinically. One clinician concern may be caseness – that the new model will diagnose a different set of PD patients from that with which they are familiar. The primary aim of this study is to determine whether this concern is valid, by testing how well the two models converge in terms of prevalence and coverage.

Participants were 305 psychiatric outpatients and 302 community residents not currently in mental-health treatment who scored above threshold on the Iowa Personality Disorder Screen (Langbehn et al., 1999). Participants were administered a semi-structured interview for DSM-5 PD, which was scored for both Section II and III PDs.

Convergence across the two PD models was variable for specific PDs, Good when specific PDs were aggregated, and Very Good for ‘any PD.’

Results provide strong evidence that the AMPD yields the same overall prevalence of PD as the current model and, further, identifies largely the same overall population. It also addresses well-known problems of the current model, is more consistent with the ICD-11 PD model, and provides more complete, individualized characterizations of persons with PD, thereby offering multiple reasons for its implementation in clinical settings.

Evidence suggests a possible relationship between exposure to childhood adversity (CA) and functional impairment in psychosis. However, the impact of CA on long-term outcomes of psychotic disorders remains poorly understood.

Two hundred and forty-three patients were assessed at their first episode of psychosis for CA and re-assessed after a mean of 21 years of follow-up for several outcome domains, including symptoms, functioning, quality of life, cognitive performance, neurological dysfunction, and comorbidity. The unique predictive ability of CA exposure for outcomes was examined using linear regression analysis controlling for relevant confounders, including socioeconomic status, family risk of schizophrenia, and obstetric complications.

There were 54% of the patients with a documented history of CA at mild or higher levels. CA experiences were more prevalent and severe in schizophrenia than in other psychotic disorders (p < 0.001). Large to very large effect sizes were observed for CA predicting most role functioning variables and negative symptoms (ΔR2 between 0.105 and 0.181). Moderate effect sizes were observed for positive symptoms, personal functioning, impaired social cognition, impaired immediate verbal learning, poor global cognition, internalized stigma, poor personal recovery, and drug abuse severity (ΔR2 between 0.040 and 0.066). A dose–response relationship was observed between levels of CA and severity of outcome domains.

Our results suggest a strong and widespread link between early adversity exposure and outcomes of psychotic disorders. Awareness of the serious long-term consequences of CA should encourage better identification of those at risk and the development of effective interventions.

Individual placement and support (IPS) is an evidence-based practice that helps individuals with mental illness gain and retain employment. IPS was implemented for young adults at a municipality level through a cross-sectoral collaboration between specialist mental healthcare, primary mental healthcare, and the government funded employment service (NAV). We investigated whether IPS implementation had a causal effect on employment outcomes for all young adults in receipt of a temporary health-related rehabilitation (work assessment allowance, WAA) welfare benefit, measured at the societal level compared to municipalities that did not implement IPS.

We used a difference in differences design to estimate the effects of IPS implementation on the outcome of workdays per year using longitudinal registry data. We estimate the average effect of being exposed to IPS implementation during four-years of implementation compared to ten control municipalities without IPS for all WAA recipients.

We found a significant, positive, causal effect on societal level employment outcomes of 5.6 (p = 0.001, 95% CI 2.7–8.4) increased workdays per year per individual, equivalent to 12.7 years of increased work in the municipality where IPS was implemented compared to municipalities without IPS. Three years after initial exposure to IPS implementation individuals worked, on average, 10.5 more days per year equating to 23.8 years of increased work.

Implementing IPS as a cross sectoral collaboration at a municipality level has a significant, positive, causal, societal impact on employment outcomes for all young adults in receipt of a temporary health-related rehabilitation welfare benefit.

While inflammation is associated with cognitive impairment in severe mental illnesses (SMI), there is substantial heterogeneity and evidence of transdiagnostic subgroups across schizophrenia (SZ) and bipolar (BD) spectrum disorders. There is however, limited knowledge about the longitudinal course of this relationship.

Systemic inflammation (C-Reactive Protein, CRP) and cognition (nine cognitive domains) was measured from baseline to 1 year follow-up in first treatment SZ and BD (n = 221), and healthy controls (HC, n = 220). Linear mixed models were used to evaluate longitudinal changes separately in CRP and cognitive domains specific to diagnostic status (SZ, BD, HC). Hierarchical clustering was applied on the entire sample to investigate the longitudinal course of transdiagnostic inflammatory-cognitive subgroups.

There were no case-control differences or change in CRP from baseline to follow-up. We confirm previous observations of case-control differences in cognition at both time-points and domain specific stability/improvement over time regardless of diagnostic status. We identified transdiagnostic inflammatory-cognitive subgroups at baseline with differing demographics and clinical severity. Despite improvement in cognition, symptoms and functioning, the higher inflammation – lower cognition subgroup (75% SZ; 48% BD; 38% HC) had sustained inflammation and lower cognition, more symptoms, and lower functioning (SMI only) at follow-up. This was in comparison to a lower inflammation – higher cognition subgroup (25% SZ, 52% BD, 62% HC), where SMI participants showed cognitive functioning at HC level with a positive clinical course.

Our findings support heterogenous and transdiagnostic inflammatory-cognitive subgroups that are stable over time, and may benefit from targeted interventions.

Adolescents often experience a heightened incidence of depressive symptoms, which can persist without early intervention. However, adolescents often struggle to identify depressive symptoms, and even when they are aware of these symptoms, seeking help is not always their immediate response. This study aimed to explore the relationship between passively collected digital data, specifically keystroke and stylus data collected via mobile devices, and the manifestation of depressive symptoms.

A total of 927 first-year middle school students from schools in Seoul solved Korean language and math problems. Throughout this study, 77 types of keystroke and stylus data were collected, including parameters such as the number of key presses, tap pressure, stroke speed, and stroke acceleration. Depressive symptoms were measured using the self-rated Patient Health Questionnaire-9 (PHQ-9).

Multiple regression analysis highlighted the significance of stroke length, speed, and acceleration, the average y-coordinate, the tap pressure, and the number of incorrect answers in relation to PHQ-9 scores. The keystroke and stylus metadata were able to reflect mood, energy, cognitive abilities, and psychomotor symptoms among adolescents with depressive symptoms.

This study demonstrates the potential of automatically collected data during school exams or classes for the early screening of clinical depressive symptoms in students. This study has the potential to serve as a cornerstone in the development of digital data frameworks for the early detection of depressive symptoms in adolescents.

Extensive research has explored altered structural and functional networks in major depressive disorder (MDD). However, studies examining the relationships between structure and function yielded heterogeneous and inconclusive results. Recent work has suggested that the structure-function relationship is not uniform throughout the brain but varies across different levels of functional hierarchy. This study aims to investigate changes in structure-function couplings (SFC) and their relevance to antidepressant response in MDD from a functional hierarchical perspective.

We compared regional SFC between individuals with MDD (n = 258) and healthy controls (HC, n = 99) using resting-state functional magnetic resonance imaging and diffusion tensor imaging. We also compared antidepressant non-responders (n = 55) and responders (n = 68, defined by a reduction in depressive severity of >50%). To evaluate variations in altered and response-associated SFC across the functional hierarchy, we ranked significantly different regions by their principal gradient values and assessed patterns of increase or decrease along the gradient axis. The principal gradient value, calculated from 219 healthy individuals in the Human Connectome Project, represents a region's position along the principal gradient axis.

Compared to HC, MDD patients exhibited increased SFC in unimodal regions (lower principal gradient) and decreased SFC in transmodal regions (higher principal gradient) (p < 0.001). Responders primarily had higher SFC in unimodal regions and lower SFC in attentional networks (median principal gradient) (p < 0.001).

Our findings reveal opposing SFC alterations in low-level unimodal and high-level transmodal networks, underscoring spatial variability in MDD pathology. Moreover, hierarchy-specific antidepressant effects provide valuable insights into predicting treatment outcomes.

To evaluate the clinical efficacy of COMPASS, a therapist-supported digital therapeutic for reducing psychological distress (anxiety/depression) in people living with long-term physical health conditions (LTCs).

A two-armed randomized-controlled trial recruiting from LTC charities. Participants with anxiety and/or depression symptoms related to their LTC(s) were randomized (concealed allocation via independent administrator) to COMPASS (access to 11 tailored modules plus five thirty-minute therapist support sessions) or standard charity support (SCS). Assessments were completed online pre-randomization, at 6- and 12-weeks post-randomization. Primary outcome was Patient Health Questionnaire Anxiety and Depression Scale; PHQ-ADS measured at 12-weeks. Analysis used intention-to-treat principles with adjusted mean differences estimated using linear mixed-effects models. Data-analyst was blinded to group allocation.

194 participants were randomized to COMPASS (N = 94) or SCS (N = 100). At 12-weeks, mean level of psychological distress was 6.82 (95% confidence interval; CI 4.55–9.10) points lower (p < 0.001) in the COMPASS arm compared with SCS (standardized mean difference of 0.71 (95% CI 0.48–0.95)). The COMPASS arm also showed moderate significant treatment effects on secondary outcomes including depression, anxiety and illness-related distress and small significant effects on functioning and quality-of-life. Rates of adverse events were comparable across the arms. Deterioration in distress at 12-weeks was observed in 2.2% of the SCS arm, and no participants in the COMPASS arm.

Compared with SCS, COMPASS digital therapeutic with minimal therapist input reduces psychological distress at post-treatment (12-weeks). COMPASS offers a potentially scalable implementation model for health services but its translation to these contexts needs further evaluating.

NCT04535778

Preserved ratio impaired spirometry (PRISm) is a new lung function impairment phenotype and has been recognized as a risk factor for various adverse outcomes. We aimed to examine the associations of this new lung function impairment phenotype with depression and anxiety in longitudinal studies.

We included 369 597 participants from the UK Biobank cohort, and divided them into population 1 without depression or anxiety and population 2 with depression or anxiety at baseline. Cox proportional hazard models were performed to evaluate the associations of lung function impairment phenotype with adverse outcomes of depression and anxiety, as well as their subtypes.

At baseline, 38 879 (10.5%) participants were diagnosed with PRISm. In population 1, the adjusted hazard ratios (HRs) for PRISm (v. normal spirometry) were 1.12 (95% CI 1.07–1.18) for incident depression, and 1.11 (95% CI 1.06–1.15) for incident anxiety, respectively. In population 2, PRISm was a risk factor for mortality in participants with depression (HR: 1.46; 95% CI 1.31–1.62) and anxiety (HR: 1.70; 95% CI 1.44–2.02), compared with normal spirometry. The magnitudes of these associations were similar in the phenotypes of lung function impairment and the subtypes of mental disorders. Trajectory analysis showed that the transition from normal spirometry to PRISm was associated with a higher risk of mortality in participants with depression and anxiety.

PRISm and airflow obstruction have similar risks of depression and anxiety. PRISm recognition may contribute to the prevention of depression and anxiety.

Individuals in a depressive episode and healthy controls exhibit robust differences on affect dynamics captured with ecological momentary assessment (EMA). However, few studies have explored affect dynamics in individuals in remission from depression, and results have been mixed.

A community sample of 18-year-olds (N = 345) completed diagnostic interviews and EMA probing emotions and low interest/motivation 5× daily for 2 weeks. Affect home base, variability, and inertia were compared across currently depressed, remitted, and never-depressed groups.

Both depression groups had a higher negative affect (NA) and low interest/motivation home base, lower positive affect (PA) home base, greater variability of NA, PA, and low interest/motivation, and greater NA and low interest/motivation inertia than never-depressed participants. Additionally, the currently depressed group had a higher sad home base specifically, greater variability across most negative emotions and low interest/motivation, and greater low interest/motivation inertia than the remitted group. The currently depressed and remitted groups did not differ in anxious, upset, or PA home base, anxious or PA variability, and inertia of all negative emotions and PA.

Findings suggest that a number of abnormalities in emotion and reward functioning persist after a depressive episode resolves, however, the tendency to experience higher levels of sadness, greater range of a variety of negative emotions, and more variable and persistent low interest/motivation are exacerbated during depressive episodes. Conversely, greater intensity and persistence of some negative emotions (anxiety, upset) and blunted positive emotions appear to equally characterize depression in both the symptomatic and remitted state.

Eating disorder (ED) research has embraced a network perspective of psychopathology, which proposes that psychiatric disorders can be conceptualized as a complex system of interacting symptoms. However, existing intervention studies using the network perspective have failed to find that symptom reductions coincide with reductions in strength of associations among these symptoms. We propose that this may reflect failure of alignment between network theory and study design and analysis. We offer hypotheses for specific symptom associations expected to be disrupted by an app-based intervention, and test sensitivity of a range of statistical metrics for identifying this intervention-induced disruption.

Data were analyzed from individuals with recurrent binge eating who participated in a randomized controlled trial of a cognitive-behavioral smartphone application. Participants were categorized into one of three groups: waitlist (n = 155), intervention responder (n = 49), and intervention non-responder (n = 77). Several statistical tests (bivariate associations, network-derived strength statistics, network invariance tests) were compared in ability to identify change in network structure.

Hypothesized disruption to specific symptom associations was observed through change in bivariate correlations from baseline to post-intervention among the responder group but were not evident from symptom and whole-of-network based network analysis statistics. Effects were masked when the intervention group was assessed together, ignoring heterogeneity in treatment responsiveness.

Findings are consistent with our contention that study design and analytic approach influence the ability to test network theory predictions with fidelity. We conclude by offering key recommendations for future network theory-driven interventional studies.

Incidence of first-episode psychosis (FEP) varies substantially across geographic regions. Phenotypes of subclinical psychosis (SP), such as psychotic-like experiences (PLEs) and schizotypy, present several similarities with psychosis. We aimed to examine whether SP measures varied across different sites and whether this variation was comparable with FEP incidence within the same areas. We further examined contribution of environmental and genetic factors to SP.

We used data from 1497 controls recruited in 16 different sites across 6 countries. Factor scores for several psychopathological dimensions of schizotypy and PLEs were obtained using multidimensional item response theory models. Variation of these scores was assessed using multi-level regression analysis to estimate individual and between-sites variance adjusting for age, sex, education, migrant, employment and relational status, childhood adversity, and cannabis use. In the final model we added local FEP incidence as a second-level variable. Association with genetic liability was examined separately.

Schizotypy showed a large between-sites variation with up to 15% of variance attributable to site-level characteristics. Adding local FEP incidence to the model considerably reduced the between-sites unexplained schizotypy variance. PLEs did not show as much variation. Overall, SP was associated with younger age, migrant, unmarried, unemployed and less educated individuals, cannabis use, and childhood adversity. Both phenotypes were associated with genetic liability to schizophrenia.

Schizotypy showed substantial between-sites variation, being more represented in areas where FEP incidence is higher. This supports the hypothesis that shared contextual factors shape the between-sites variation of psychosis across the spectrum.

Mild cognitive deficits (MCD) emerge before the first episode of psychosis (FEP) and persist in the clinical high-risk (CHR) stage. This study aims to refine risk prediction by developing MCD models optimized for specific early psychosis stages and target populations.

A comprehensive neuropsychological battery assessed 1059 individuals with FEP, 794 CHR, and 774 matched healthy controls (HCs). CHR subjects, followed up for 2 years, were categorized into converters (CHR-C) and non-converters (CHR-NC). The MATRICS Consensus Cognitive Battery standardized neurocognitive tests were employed.

Both the CHR and FEP groups exhibited significantly poorer performance compared to the HC group across all neurocognitive tests (all p < 0.001). The CHR-C group demonstrated poorer performance compared to the CHR-NC group on three sub-tests: visuospatial memory (p < 0.001), mazes (p = 0.005), and symbol coding (p = 0.023) tests. Upon adjusting for sex and age, the performance of the MCD model was excellent in differentiating FEP from HC, as evidenced by an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.895 (p < 0.001). However, when applied in the CHR group for predicting CHR-C (AUC = 0.581, p = 0.008), the performance was not satisfactory. To optimize the efficiency of psychotic risk assessment, three distinct MCD models were developed to distinguish FEP from HC, predict CHR-C from CHR-NC, and identify CHR from HC, achieving accuracies of 89.3%, 65.6%, and 80.2%, respectively.

The MCD exhibits variations in domains, patterns, and weights across different stages of early psychosis and diverse target populations. Emphasizing precise risk assessment, our findings highlight the importance of tailored MCD models for different stages and risk levels.

Access to psychedelic drugs is liberalizing, yet responses are highly unpredictable. It is therefore imperative that we improve our ability to predict the nature of the acute psychedelic experience to improve safety and optimize potential therapeutic outcomes. This study sought to validate the ‘Imperial Psychedelic Predictor Scale’ (IPPS), a short, widely applicable, prospective measure intended to be predictive of salient dimensions of the psychedelic experience.

Using four independent datasets in which the IPPS was completed prospectively – two online surveys of ‘naturalistic’ use (N = 741, N = 836) and two controlled administration datasets (N = 30, N = 28) – we conducted factor analysis, regression, and correlation analyses to assess the construct, predictive, and convergent validity of the IPPS.

Our approach produced a 9-item scale with good internal consistency (Cronbach's α = 0.8) containing three factors: set, rapport, and intention. The IPPS was significantly predictive of ‘mystical’, ‘challenging’, and ‘emotional breakthrough’ experiences. In a controlled administration dataset (N = 28), multiple regression found set and rapport explaining 40% of variance in mystical experience, and simple regression found set explained 16% of variance in challenging experience. In another (N = 30), rapport was related to emotional breakthrough explaining 9% of variance.

Together, these data suggest that the IPPS is predictive of relevant acute features of the psychedelic experience in a broad range of contexts. We hope that this brief 9-item scale will be widely adopted for improved knowledge of psychedelic preparedness in controlled settings and beyond.

Different aspects of social relationships (e.g., social network size or loneliness) have been associated with dementia risk, while their overlap and potentially underlying pathways remain largely unexplored. This study therefore aimed to (1) discriminate between different facets of social relationships by means of factor analysis, (2) examine their associations with dementia risk, and (3) assess mediation by depressive symptoms.

Thirty-six items from questionnaires on social relationships administered in Wave 2 (2004/2005) of the English Longitudinal Study of Ageing (n = 7536) were used for exploratory and confirmatory factor analysis. Factors were then used as predictors in Cox proportional hazard models with dementia until Wave 9 as outcome, adjusted for demographics and cardiovascular risk factors. Structural equation modeling tested mediation by depressive symptoms through effect decomposition.

Factor analyses identified six social factors. Across a median follow-up time of 11.8 years (IQR = 5.9–13.9 years), 501 people developed dementia. Higher factor scores for frequency and quality of contact with children (HR = 0.88; p = 0.021) and more frequent social activity engagement (HR = 0.84; p < 0.001) were associated with lower dementia risk. Likewise, higher factor scores for loneliness (HR = 1.13; p = 0.011) and negative experiences of social support (HR = 1.10; p = 0.047) were associated with higher dementia risk. Mediation analyses showed a significant partial effect mediation by depressive symptoms for all four factors. Additional analyses provided little evidence for reverse causation.

Frequency and quality of social contacts, social activity engagement, and feelings of loneliness are associated with dementia risk and might be suitable targets for dementia prevention programs, partly by lowering depressive symptoms.

A minority of naturally cycling individuals experience clinically significant affective changes across the menstrual cycle. However, few studies have examined cognitive and behavioral constructs that may maintain or worsen these changes. Several small studies link rumination with premenstrual negative affect, with authors concluding that a tendency to ruminate amplifies and perpetuates hormone-sensitive affective symptoms. Replication in larger samples is needed to confirm the validity of rumination as a treatment target.

190 cycling individuals (M = 30.82 years; 61.1% Caucasian) were recruited for moderate perceived stress, a risk factor for cyclical symptoms. They completed the Rumination Response Scale at baseline, then reported daily affective and physical symptoms across 1–6 cycles. Multilevel growth models tested trait rumination as a predictor of baseline levels, luteal increases, and follicular decreases in symptoms.

The degree of affective cyclicity was normally distributed across a substantial range, supporting feasibility of hypothesis tests and validating the concept of dimensional hormone sensitivity. Contrary to prediction, higher brooding did not predict levels or cyclical changes of any symptom. In a subsample selected for luteal increases in negative affect, brooding predicted higher baseline negative affect but still did not predict affective cyclicity.

An individual's trait-like propensity to engage in rumination may not be a valid treatment target in premenstrual mood disorders. State-like changes in rumination should still be further explored, and well-powered prospective studies should explore other cognitive and behavioral factors to inform development of targeted psychological treatments for patients with cyclical affective symptoms.

Major depressive disorder (MDD) is the leading cause of disability globally, with moderate heritability and well-established socio-environmental risk factors. Genetic studies have been mostly restricted to European settings, with polygenic scores (PGS) demonstrating low portability across diverse global populations.

This study examines genetic architecture, polygenic prediction, and socio-environmental correlates of MDD in a family-based sample of 10 032 individuals from Nepal with array genotyping data. We used genome-based restricted maximum likelihood to estimate heritability, applied S-LDXR to estimate the cross-ancestry genetic correlation between Nepalese and European samples, and modeled PGS trained on a GWAS meta-analysis of European and East Asian ancestry samples.

We estimated the narrow-sense heritability of lifetime MDD in Nepal to be 0.26 (95% CI 0.18–0.34, p = 8.5 × 10−6). Our analysis was underpowered to estimate the cross-ancestry genetic correlation (rg = 0.26, 95% CI −0.29 to 0.81). MDD risk was associated with higher age (beta = 0.071, 95% CI 0.06–0.08), female sex (beta = 0.160, 95% CI 0.15–0.17), and childhood exposure to potentially traumatic events (beta = 0.050, 95% CI 0.03–0.07), while neither the depression PGS (beta = 0.004, 95% CI −0.004 to 0.01) or its interaction with childhood trauma (beta = 0.007, 95% CI −0.01 to 0.03) were strongly associated with MDD.

Estimates of lifetime MDD heritability in this Nepalese sample were similar to previous European ancestry samples, but PGS trained on European data did not predict MDD in this sample. This may be due to differences in ancestry-linked causal variants, differences in depression phenotyping between the training and target data, or setting-specific environmental factors that modulate genetic effects. Additional research among under-represented global populations will ensure equitable translation of genomic findings.

Many autistic people in mental health are suicidal. This study evaluated the effectiveness of dialectical behavior therapy (DBT) v. treatment as usual (TAU) in reducing suicidal ideation and suicide attempts.

At six Dutch mental health centers, 123 outpatients (18–65 years) with DSM-5 diagnosed autism spectrum disorder (ASD) and suicidal behavior were randomly assigned to the DBT intervention group (n = 63) or TAU control group (n = 60). Assessments were conducted at baseline, post-treatment at 6 months and 12-month follow-up. The primary outcomes were severity of suicidal ideation and frequency of suicide attempts. The severity of depression and social anxiety were secondary outcomes.

At end-of-treatment, DBT significantly reduced both suicidal ideation (z = −2.24; p = 0.025; b = −4.41; s.e. = 197.0) and suicide attempts (z = −3.15; p = 0.002; IRR = 0.046; s.e. = 0.045) compared to TAU, but lost statistical significance at the 12-month follow-up. Depression severity significantly decreased with DBT (z = −1.99; p = 0.046: b = −2.74; s.e. = 1.37) remaining so at 12 months (z = −2.46; p = 0.014; b = −3.37; s.e. = 1.37). No effects were observed on social anxiety. Severe adverse events included two suicides in the TAU condition.

DBT is an acceptable, safe, and short-term effective intervention to reduce suicidal ideation and suicide attempts in autistic adults with suicidal behavior.

Physical sequelae of anorexia nervosa (AN) include a marked reduction in whole brain volume and subcortical structures such as the hippocampus. Previous research has indicated aberrant levels of inflammatory markers and growth factors in AN, which in other populations have been shown to influence hippocampal integrity.

Here we investigated the influence of concentrations of two pro-inflammatory cytokines (tumor necrosis factor-alpha [TNF-α] and interleukin-6 [IL-6]) and brain-derived neurotrophic factor (BDNF) on the whole hippocampal volume, as well as the volumes of three regions (the hippocampal body, head, and tail) and 18 subfields bilaterally. Investigations occurred both cross-sectionally between acutely underweight adolescent/young adult females with AN (acAN; n = 82) and people recovered from AN (recAN; n = 20), each independently pairwise age-matched with healthy controls (HC), and longitudinally in acAN after partial renourishment (n = 58). Hippocampal subfield volumes were quantified using FreeSurfer. Concentrations of molecular factors were analyzed in linear models with hippocampal (subfield) volumes as the dependent variable.

Cross-sectionally, there was no evidence for an association between IL-6, TNF-α, or BDNF and between-group differences in hippocampal subfield volumes. Longitudinally, increasing concentrations of BDNF were positively associated with longitudinal increases in bilateral global hippocampal volumes after controlling for age, age2, estimated total intracranial volume, and increases in body mass index (BMI).

These findings suggest that increases in BDNF may contribute to global hippocampal recovery over and above increases in BMI during renourishment. Investigations into treatments targeted toward increasing BDNF in AN may be warranted.

Previous observational epidemiological studies have suggested that coffee consumption during pregnancy may affect fetal neurodevelopment. However, results are inconsistent and may represent correlational rather than causal relationships. The present study investigated whether maternal coffee consumption was observationally associated and causally related to offspring childhood neurodevelopmental difficulties (NDs) in the Norwegian Mother, Father and Child Cohort Study.

The observational relationships between maternal/paternal coffee consumption (before and during pregnancy) and offspring NDs were assessed using linear regression analyses (N = 58694 mother-child duos; N = 22 576 father-child duos). To investigate potential causal relationships, individual-level (N = 46 245 mother-child duos) and two-sample Mendelian randomization (MR) analyses were conducted using genetic variants previously associated with coffee consumption as instrumental variables.

We observed positive associations between maternal coffee consumption and offspring difficulties with social-communication/behavioral flexibility, and inattention/hyperactive-impulsive behavior (multiple testing corrected p < 0.005). Paternal coffee consumption (negative control) was not observationally associated with the outcomes. After adjusting for potential confounders (smoking, alcohol, education and income), the maternal associations attenuated to the null. MR analyses suggested that increased maternal coffee consumption was causally associated with social-communication difficulties (individual-level: beta = 0.128, se = 0.043, p = 0.003; two-sample: beta = 0.348, se = 0.141, p = 0.010). However, individual-level MR analyses that modelled potential pleiotropic pathways found the effect diminished (beta = 0.088, se = 0.049, p = 0.071). Individual-level MR analyses yielded similar estimates (heterogeneity p = 0.619) for the causal effect of coffee consumption on social communication difficulties in maternal coffee consumers (beta = 0.153, se = 0.071, p = 0.032) and non-consumers (beta = 0.107, se = 0.134, p = 0.424).

Together, our results provide little evidence for a causal effect of maternal coffee consumption on offspring NDs.

Although the Department of Veterans Affairs (VA) has made important suicide prevention advances, efforts primarily target high-risk patients with documented suicide risk, such as suicidal ideation, prior suicide attempts, and recent psychiatric hospitalization. Approximately 90% of VA patients that go on to die by suicide do not meet these high-risk criteria and therefore do not receive targeted suicide prevention services. In this study, we used national VA data to focus on patients that were not classified as high-risk, but died by suicide.

Our sample included all VA patients who died by suicide in 2017 or 2018. We determined whether patients were classified as high-risk using the VA's machine learning risk prediction algorithm. After excluding these patients, we used principal component analysis to identify moderate-risk and low-risk patients and investigated demographics, service-usage, diagnoses, and social determinants of health differences across high-, moderate-, and low-risk subgroups.

High-risk (n = 452) patients tended to be younger, White, unmarried, homeless, and have more mental health diagnoses compared to moderate- (n = 2149) and low-risk (n = 2209) patients. Moderate- and low-risk patients tended to be older, married, Black, and Native American or Pacific Islander, and have more physical health diagnoses compared to high-risk patients. Low-risk patients had more missing data than higher-risk patients.

Study expands epidemiological understanding about non-high-risk suicide decedents, historically understudied and underserved populations. Findings raise concerns about reliance on machine learning risk prediction models that may be biased by relative underrepresentation of racial/ethnic minorities within health system.