A large and accumulating body of evidence shows that loneliness is detrimental for various health and well-being outcomes. However, less is known about potentially modifiable factors that lead to decreased loneliness.

We used data from the Health and Retirement Study to prospectively evaluate a wide array of candidate predictors of subsequent loneliness. Importantly, we examined if changes in 69 physical-, behavioral-, and psychosocial-health factors (from t0;2006/2008 to t1;2010/2012) were associated with subsequent loneliness 4 years later (t2;2014/2016).

Adjusting for a large range of covariates, changes in certain health behaviors (e.g. increased physical activity), physical health factors (e.g. fewer functioning limitations), psychological factors (e.g. increased purpose in life, decreased depression), and social factors (e.g. greater number of close friends) were associated with less subsequent loneliness.

Our findings suggest that subjective ratings of physical and psychological health and perceived social environment (e.g. chronic pain, self-rated health, purpose in life, anxiety, neighborhood cohesion) are more strongly associated with subsequent loneliness. Yet, objective ratings (e.g. specific chronic health conditions, living status) show less evidence of associations with subsequent loneliness. The current study identified potentially modifiable predictors of subsequent loneliness that may be important targets for interventions aimed at reducing loneliness.

Individuals with bipolar disorder are commonly correctly diagnosed a decade after symptom onset. Machine learning techniques may aid in early recognition and reduce the disease burden. As both individuals at risk and those with a manifest disease display structural brain markers, structural magnetic resonance imaging may provide relevant classification features.

Following a pre-registered protocol, we trained linear support vector machine (SVM) to classify individuals according to their estimated risk for bipolar disorder using regional cortical thickness of help-seeking individuals from seven study sites (N = 276). We estimated the risk using three state-of-the-art assessment instruments (BPSS-P, BARS, EPIbipolar).

For BPSS-P, SVM achieved a fair performance of Cohen's κ of 0.235 (95% CI 0.11–0.361) and a balanced accuracy of 63.1% (95% CI 55.9–70.3) in the 10-fold cross-validation. In the leave-one-site-out cross-validation, the model performed with a Cohen's κ of 0.128 (95% CI −0.069 to 0.325) and a balanced accuracy of 56.2% (95% CI 44.6–67.8). BARS and EPIbipolar could not be predicted. In post hoc analyses, regional surface area, subcortical volumes as well as hyperparameter optimization did not improve the performance.

Individuals at risk for bipolar disorder, as assessed by BPSS-P, display brain structural alterations that can be detected using machine learning. The achieved performance is comparable to previous studies which attempted to classify patients with manifest disease and healthy controls. Unlike previous studies of bipolar risk, our multicenter design permitted a leave-one-site-out cross-validation. Whole-brain cortical thickness seems to be superior to other structural brain features.

Research using latent variable models demonstrates that pre-attentive measures of early auditory processing (EAP) and cognition may initiate a cascading effect on daily functioning in schizophrenia. However, such models fail to account for relationships among individual measures of cognition and EAP, thereby limiting their utility. Hence, EAP and cognition may function as complementary and interacting measures of brain function rather than independent stages of information processing. Here, we apply a data-driven approach to identifying directional relationships among neurophysiologic and cognitive variables.

Using data from the Consortium on the Genetics of Schizophrenia 2, we estimated Gaussian Graphical Models and Bayesian networks to examine undirected and directed connections between measures of EAP, including mismatch negativity and P3a, and cognition in 663 outpatients with schizophrenia and 630 control participants.

Chain structures emerged among EAP and attention/vigilance measures in schizophrenia and control groups. Concerning differences between the groups, object memory was an influential variable in schizophrenia upon which other cognitive domains depended, and working memory was an influential variable in controls.

Measures of EAP and attention/vigilance are conditionally independent of other cognitive domains that were used in this study. Findings also revealed additional causal assumptions among measures of cognition that could help guide statistical control and ultimately help identify early-stage targets or surrogate endpoints in schizophrenia.

Although numerous studies have examined the effects of psychological treatments for obsessive-compulsive disorder (OCD), their overall effectiveness remains unclear. We aimed to estimate their overall effect by combining all available randomized controlled trials (RCTs) comparing psychological treatments to control groups for OCD.

We conducted a meta-analysis of 48 RCTs with 55 comparisons published between 1992 and 1 January 2023. The primary outcome was OCD symptom severity, with Hedges' g calculated at post-treatment and follow-up. Random-effects models were employed for all analyses, and the risk of bias was assessed.

In general, psychological treatments demonstrated a significantly large effect (g = −1.14; 95% CI [−1.31 to −0.97]; I2 = 72.23%) on reducing OCD symptom severity post-treatment, this finding remained consistent across measures and after excluding outliers, but lost significance in the sensitivity analysis for only studies with low risk of bias. Type of treatment, control group and treatment format were associated with treatment effects. Moreover, more severe baseline OCD symptom severity predicted higher degree of treatment efficacy. No significant differences were observed in dropout rates between the treatment and control groups. Treatment effects lost significance at 3–6 and 6–12 month follow-ups. 87% of RCTs were rated at high risk of bias.

Psychological treatments are effective in reducing OCD symptom severity. However, caution should be exercised when interpreting these results due to the high heterogeneity and risk of bias across RCTs. Future studies with more rigorous methodology are required, as well as studies examining their long-term effectiveness.

Despite the growing interest in the prevalence and consequences of loneliness, the way it is measured still raises a number of questions. In particular, few studies have directly compared the psychometric properties of very short measures of loneliness to standard measures.

We conducted a large epidemiological study of midwife students (n = 1742) and performed a head-to-head comparison of the psychometric properties of the standard (20 items) and short version (3 items) of the UCLA Loneliness Scales (UCLA-LS). All participants completed the UCLA-LS-20, UCLA-LS-3, as well as other measures of mental health, including anxiety and depression.

First, as predicted, we found that the two loneliness scales were strongly associated with each other. Second, when using the dimensional scores of the scales, we showed that the internal reliability, convergent-, discriminant-, and known-groups validities were high and of similar magnitude between the UCLA-LS-20 and the UCLA-LS-3. Third, when the scales were dichotomized, the results were more mixed. The sensitivity and/or specificity of the UCLA-LS-3 against the UCLA-LS-20 were systematically below acceptable thresholds, regardless of the dichotomizing process used. In addition, the prevalence of loneliness was strikingly variable as a function of the cut-offs used.

Overall, we showed that the UCLA-LS-3 provided an adequate dimensional measure of loneliness that is very similar to the UCLA-LS-20. On the other hand, we were able to highlight more marked differences between the scales when their scores were dichotomized, which has important consequences for studies estimating, for example, the prevalence of loneliness.

We investigate if covariation between parental and child attention-deficit hyperactivity disorder (ADHD) behaviors can be explained by environmental and/or genetic transmission.

We employed a large children-of-twins-and-siblings sample (N = 22 276 parents and 11 566 8-year-old children) of the Norwegian Mother, Father and Child Cohort Study. This enabled us to disentangle intergenerational influences via parental genes and parental behaviors (i.e. genetic and environmental transmission, respectively). Fathers reported on their own symptoms and mothers on their own and their child's symptoms.

Child ADHD behaviors correlated with their mother's (0.24) and father's (0.10) ADHD behaviors. These correlations were largely due to additive genetic transmission. Variation in children's ADHD behaviors was explained by genetic factors active in both generations (11%) and genetic factors specific to the children (46%), giving a total heritability of 57%. There were small effects of parental ADHD behaviors (2% environmental transmission) and gene–environment correlation (3%). The remaining variability in ADHD behaviors was due to individual-specific environmental factors.

The intergenerational resemblance of ADHD behaviors is primarily due to genetic transmission, with little evidence for parental ADHD behaviors causing children's ADHD behaviors. This contradicts theories proposing environmental explanations of intergenerational transmission of ADHD, such as parenting theories or psychological life-history theory.

Laboratory paradigms are widely used to study fear learning in posttraumatic stress disorder (PTSD). Recent basic science models demonstrate that, during fear learning, patterns of activity in large neuronal ensembles for the conditioned stimuli (CS) begin to reinstate neural activity patterns for the unconditioned stimuli (US), suggesting a direct way of quantifying fear memory strength for the CS. Here, we translate this concept to human neuroimaging and test the impact of post-learning dopaminergic neurotransmission on fear memory strength during fear acquisition, extinction, and recall among women with PTSD in a re-analysis of previously reported data.

Participants (N = 79) completed a context-dependent fear acquisition and extinction task on day 1 and extinction recall tests 24 h later. We decoded activity patterns in large-scale functional networks for the US, then applied this decoder to activity patterns toward the CS on day 1 and day 2.

US decoder output for the CS+ increased during acquisition and decreased during extinction in networks traditionally implicated in human fear learning. The strength of US neural reactivation also predicted individuals skin conductance responses. Participants randomized to receive L-DOPA (n = 43) following extinction on day 1 demonstrated less US neural reactivation on day 2 relative to the placebo group (n = 28).

These results support neural reactivation as a measure of memory strength between competing memories of threat and safety and further demonstrate the role of dopaminergic neurotransmission in the consolidation of fear extinction memories.

The neural correlates underlying late-life depressive symptoms and cognitive deterioration are largely unclear, and little is known about the role of chronic physical conditions in such association. This research explores both concurrent and longitudinal associations between late-life depressive symptoms and cognitive functions, with examining the neural substrate and chronic vascular diseases (CVDs) in these associations.

A total of 4109 participants (mean age = 65.4, 63.0% females) were evaluated for cognitive functions through various neuropsychological assessments. Depressive symptoms were assessed by the Geriatric Depression Scale and CVDs were self-reported. T1-weighted magnetic resonance imaging (MRI), diffusion tensor imaging, and functional MRI (fMRI) data were acquired in a subsample (n = 791).

Cognitively, higher depressive symptoms were correlated with poor performance across all cognitive domains, with the strongest association with episodic memory (r = ‒0.138, p < 0.001). Regarding brain structure, depressive symptoms were negatively correlated with thalamic volume and white matter integrity. Further, white matter integrity was found to mediate the longitudinal association between depressive symptoms and episodic memory (indirect effect = −0.017, 95% CI −0.045 to −0.002) and this mediation was only significant for those with severe CVDs (β = −0.177, p = 0.008).

This study is one of the first to provide neural evidence elucidating the longitudinal associations between late-life depressive symptoms and cognitive dysfunction. Additionally, the severity of CVDs strengthened these associations, which enlightens the potential of managing CVDs as an intervention target for preventing depressive symptoms-related cognitive decline.

Suicide attempts are a moderately heritable trait, and genetic correlations with psychiatric and related intermediate phenotypes have been reported. However, as several mental disorders as well as major depressive disorder (MDD) are strongly associated with suicide attempts, these genetic correlations could be mediated by psychiatric disorders. Here, we investigated genetic correlations of suicide attempts with psychiatric and related intermediate phenotypes, with and without adjusting for mental disorders.

To investigate the genetic correlations, we utilized large-scale genome-wide association study summary statistics for suicide attempts (with and without adjusting for mental disorders), nine psychiatric disorders, and 15 intermediate phenotypes.

Without adjusting for mental disorders, suicide attempts had significant positive genetic correlations with risks of attention-deficit/hyperactivity disorder, schizophrenia, bipolar disorder, MDD, anxiety disorders and posttraumatic stress disorder; higher risk tolerance; earlier age at first sexual intercourse, at first birth and at menopause; higher parity; lower childhood IQ, educational attainment and cognitive ability; and lower smoking cessation. After adjusting for mental disorders, suicide attempts had significant positive genetic correlations with the risk of MDD; earlier age at first sexual intercourse, at first birth and at menopause; and lower educational attainment. After adjusting for mental disorders, most of the genetic correlations with psychiatric disorders were decreased, while several genetic correlations with intermediate phenotypes were increased.

These findings highlight the importance of considering mental disorders in the analysis of genetic correlations related to suicide attempts and suggest that susceptibility to MDD, reproductive behaviors, and lower educational levels share a genetic basis with suicide attempts after adjusting for mental disorders.

Studies suggest severe mental disorders (SMDs), such as schizophrenia, major depressive disorder and bipolar disorder, are associated with common alterations in brain activity, albeit with a graded level of impairment. However, discrepancies between study findings likely to results from both small sample sizes and the use of different functional magnetic resonance imaging (fMRI) tasks. To address these issues, data-driven meta-analytic approach designed to identify homogeneous brain co-activity patterns across tasks was conducted to better characterize the common and distinct alterations between these disorders.

A hierarchical clustering analysis was conducted to identify groups of studies reporting similar neuroimaging results, independent of task type and psychiatric diagnosis. A traditional meta-analysis (activation likelihood estimation) was then performed within each of these groups of studies to extract their aberrant activation maps.

A total of 762 fMRI study contrasts were targeted, comprising 13 991 patients with SMDs. Hierarchical clustering analysis identified 5 groups of studies (meta-analytic groupings; MAGs) being characterized by distinct aberrant activation patterns across SMDs: (1) emotion processing; (2) cognitive processing; (3) motor processes, (4) reward processing, and (5) visual processing. While MAG1 was mostly commonly impaired, MAG2 was more impaired in schizophrenia, while MAG3 and MAG5 revealed no differences between disorder. MAG4 showed the strongest between-diagnoses differences, particularly in the striatum, posterior cingulate cortex, and ventromedial prefrontal cortex.

SMDs are characterized mostly by common deficits in brain networks, although differences between disorders are also present. This study highlights the importance of studying SMDs simultaneously rather than independently.

Attitudes toward risk and ambiguity significantly influence how individuals assess and value rewards. This fMRI study examines the reward valuation process under conditions of uncertainty and investigates the associated neural mechanisms in individuals who engage in nonsuicidal self-injury (NSSI) as a coping mechanism for psychological pain.

The study involved 44 unmedicated individuals who reported five or more NSSI episodes in the past year, along with 42 age-, sex-, handedness-, IQ-, and socioeconomic status-matched controls. During the fMRI scans, all participants were presented with decision-making scenarios involving uncertainty, both in terms of risk (known probabilities) and ambiguity (unknown probabilities).

In the NSSI group, aversive attitudes toward ambiguity were correlated with increased emotion reactivity and greater method versatility. Whole-brain analysis revealed notable group-by-condition interactions in the right middle cingulate cortex and left hippocampus. Specifically, the NSSI group showed decreased neural activation under ambiguity v. risk compared to the control group. Moreover, reduced hippocampal activation under ambiguity in the NSSI group was associated with increased emotion regulation problems.

This study presents the first evidence of reduced brain activity in specific regions during value-based decision-making under conditions of ambiguity in individuals with NSSI. These findings have important clinical implications, particularly concerning emotion dysregulation in this population. This study indicates the need for interventions that support and guide individuals with NSSI to promote adaptive decision-making in the face of ambiguous uncertainty.

The clinical course of major depressive disorder (MDD) is heterogeneous, and early-onset MDD often has a more severe and complex clinical course. Our goal was to determine whether polygenic scores (PGSs) for psychiatric disorders are associated with treatment trajectories in early-onset MDD treated in secondary care.

Data were drawn from the iPSYCH2015 sample, which includes all individuals born in Denmark between 1981 and 2008 who were treated in secondary care for depression between 1995 and 2015. We selected unrelated individuals of European ancestry with an MDD diagnosis between ages 10–25 (N = 10577). Seven-year trajectories of hospital contacts for depression were modeled using Latent Class Growth Analysis. Associations between PGS for MDD, bipolar disorder, schizophrenia, ADHD, and anorexia and trajectories of MDD contacts were modeled using multinomial logistic regressions.

We identified four trajectory patterns: brief contact (65%), prolonged initial contact (20%), later re-entry (8%), and persistent contact (7%). Relative to the brief contact trajectory, higher PGS for ADHD was associated with a decreased odds of membership in the prolonged initial contact (odds ratio = 1.06, 95% confidence interval = 1.01–1.11) and persistent contact (1.12, 1.03–1.21) trajectories, while PGS-AN was associated with increased odds of membership in the persistent contact trajectory (1.12, 1.03–1.21).

We found significant associations between polygenic liabilities for psychiatric disorders and treatment trajectories in patients with secondary-treated early-onset MDD. These findings help elucidate the relationship between a patient's genetics and their clinical course; however, the effect sizes are small and therefore unlikely to have predictive value in clinical settings.

Despite their documented efficacy, substantial proportions of patients discontinue antidepressant medication (ADM) without a doctor's recommendation. The current report integrates data on patient-reported reasons into an investigation of patterns and predictors of ADM discontinuation.

Face-to-face interviews with community samples from 13 countries (n = 30 697) in the World Mental Health (WMH) Surveys included n = 1890 respondents who used ADMs within the past 12 months.

10.9% of 12-month ADM users reported discontinuation-based on recommendation of the prescriber while 15.7% discontinued in the absence of prescriber recommendation. The main patient-reported reason for discontinuation was feeling better (46.6%), which was reported by a higher proportion of patients who discontinued within the first 2 weeks of treatment than later. Perceived ineffectiveness (18.5%), predisposing factors (e.g. fear of dependence) (20.0%), and enabling factors (e.g. inability to afford treatment cost) (5.0%) were much less commonly reported reasons. Discontinuation in the absence of prescriber recommendation was associated with low country income level, being employed, and having above average personal income. Age, prior history of psychotropic medication use, and being prescribed treatment from a psychiatrist rather than from a general medical practitioner, in comparison, were associated with a lower probability of this type of discontinuation. However, these predictors varied substantially depending on patient-reported reasons for discontinuation.

Dropping out early is not necessarily negative with almost half of individuals noting they felt better. The study underscores the diverse reasons given for dropping out and the need to evaluate how and whether dropping out influences short- or long-term functioning.

Major depression is associated with changes in plasma L-carnitine and acetyl-L-carnitine. But its association with acylcarnitines remains unclear. The aim of this study was to assess metabolomic profiles of 38 acylcarnitines in patients with major depression before and after treatment compared to healthy controls (HCs).

Metabolomic profiles of 38 plasma short-, medium-, and long-chain acylcarnitines were performed by liquid chromatography-mass spectrometry in 893 HCs from the VARIETE cohort and 460 depressed patients from the METADAP cohort before and after 6 months of antidepressant treatment.

As compared to HCs, depressed patients had lower levels of medium- and long-chain acylcarnitines. After 6 months of treatment, increased levels of medium- and long-chain acyl-carnitines were observed that no longer differed from those of controls. Accordingly, several medium- and long-chain acylcarnitines were negatively correlated with depression severity.

These medium- and long-chain acylcarnitine dysregulations argue for mitochondrial dysfunction through fatty acid β-oxidation impairment during major depression.

Response inhibition − or the ability to withhold a suboptimal response − relies on the efficacy of fronto-striatal networks, and is impaired in neuropsychiatric disorders including addiction. Cortical paired associative stimulation (cPAS) is a form of transcranial magnetic stimulation (TMS) which can strengthen neuronal connections via spike-timing-dependent plasticity mechanisms. Here, we used cPAS targeting the fronto-striatal inhibitory network to modulate performance on a response inhibition measure in chronic alcohol use.

Fifty-five participants (20 patients with a formal alcohol use disorder (AUD) diagnosis (26–74 years, 6[30%] females) and 20 matched healthy controls (HCs) (27–73 years, 6[30%] females) within a larger sample of 35 HCs (23–84 years, 11[31.4%] females) underwent two randomized sessions of cPAS 1-week apart: right inferior frontal cortex stimulation preceding right presupplementary motor area stimulation by either 4 ms (excitation condition) or 100 ms (control condition), and were subsequently administered the Stop Signal Task (SST) in both sessions.

HCs showed decreased stop signal reaction time in the excitation condition (t(19) = −3.01, p = 0.007, [CIs]:−35.6 to −6.42); this facilitatory effect was not observed for AUD (F(1,31) = 9.57, p = 0.004, CIs: −68.64 to −14.11). Individually, rates of SST improvement were substantially higher for healthy (72%) relative to AUD (13.6%) groups (OR: 2.33, p = 0.006, CIs:−3.34 to −0.55).

In line with previous findings, cPAS improved response inhibition in healthy adults by strengthening the fronto-striatal network through putative long-term potentiation-like plasticity mechanisms. Furthermore, we identified a possible marker of impaired cortical excitability, and, thus, diminished capacity for cPAS-induced neuroplasticity in AUD with direct implications to a disorder-relevant cognitive process.

Peer victimization predicts the development of mental health symptoms in the transition to adolescence, but it is unclear whether and how parents and school environments can buffer this link.

We analyzed two-year longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study, involving a diverse sample of 11 844 children across the United States (average at baseline = 9.91 years; standard deviation = 0.63; range = 8.92–11.08; complete case sample = 8385). Longitudinal associations between peer victimization and two-year changes in mental health symptoms of major depression disorder (MDD), separation anxiety (SA), prodromal psychosis (PP), and attention-deficit/hyperactivity disorder (ADHD) were examined including a wide range of covariates. Mixed linear models were used to test for the moderating effects of parental warmth and prosocial school environment.

20% of children experienced peer victimization. Higher exposure to peer victimization was associated with increases in MDD, SA, and ADHD symptoms. Parental warmth was associated with decreases in MDD symptoms but did not robustly buffer the link between peer victimization and mental health symptoms. Prosocial school environment predicted decreases in PP symptoms and buffered the link between peer victimization and MDD symptoms but amplified the link between peer victimization and SA and ADHD symptoms.

Peer victimization is associated with increases in mental health symptoms during the transition to adolescence. Parental warmth and prosocial school environments might not be enough to counter the negative consequences of peer victimization on all mental health outcomes.

There is growing evidence that gray matter atrophy is constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true in individuals with depression remains unknown. In this study, we aimed to investigate the association between gray matter atrophy and normal connectome architecture at individual level in depression.

In this study, 297 patients with depression and 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery dataset (105 never-treated first-episode patients and matched 130 HCs) and a replication dataset (106 patients and matched 126 HCs). For each patient, individualized regional atrophy was assessed using normative model and brain regions whose structural connectome profiles in HCs most resembled the atrophy patterns were identified as putative epicenters using a backfoward stepwise regression analysis.

In general, the structural connectome architecture of the identified disease epicenters significantly explained 44% (±16%) variance of gray matter atrophy. While patients with depression demonstrated tremendous interindividual variations in the number and distribution of disease epicenters, several disease epicenters with higher participation coefficient than randomly selected regions, including the hippocampus, thalamus, and medial frontal gyrus were significantly shared by depression. Other brain regions with strong structural connections to the disease epicenters exhibited greater vulnerability. In addition, the association between connectome and gray matter atrophy uncovered two distinct subgroups with different ages of onset.

These results suggest that gray matter atrophy is constrained by structural brain connectome and elucidate the possible pathological progression in depression.

Individuals with schizophrenia spectrum and related psychotic disorders (SSD) experience significant impairments in social cognition that impede functioning. Social cognition is a multidimensional construct consisting of four domains: 1. theory of mind, 2. emotion processing, 3. attributional style and 4. social perception. Metacognitive training (MCT) is an intervention designed to target cognitive biases in psychosis containing two modules addressing social cognition.

A systematic review and meta-analysis was conducted to investigate the effects of MCT on social cognition and two of its domains: theory of mind and emotion processing. Ten electronic databases were scoured from 2007 to 1 February 2022 for MCT studies reporting social cognition outcomes for people with SSD (1050 identified, 282 assessed). Effect sizes were calculated using Cohen's d in R.

Nine studies were included in the meta-analysis (nMCT = 212, ncontrol = 194). MCT had a small but positive effect on global social cognition (d = 0.28 [95% CI 0.07–0.49]) and theory of mind (d = 0.27 [95% CI 0.01–0.52]). MCT showed no evidence of an effect on emotion processing (d = 0.03 [95% CI –0.26 to 0.32]).

MCT has a small but significant effect on social cognition for people with SSD. Our results add to other recent meta-analyses showing significant effects of MCT on clinically relevant outcomes such as positive symptoms, cognitive biases and cognitive insight. We recommend that future studies on MCT report outcomes on all four domains of social cognition.

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