Aberrant brain connectivity during emotional processing, especially within the fronto-limbic pathway, is one of the hallmarks of major depressive disorder (MDD). However, the methodological heterogeneity of previous studies made it difficult to determine the functional and etiological implications of specific alterations in brain connectivity. We previously reported alterations in psychophysiological interaction measures during emotional face processing, distinguishing depressive pathology from at-risk/resilient and healthy states. Here, we extended these findings by effective connectivity analyses in the same sample to establish a refined neural model of emotion processing in depression.

Thirty-seven patients with MDD, 45 first-degree relatives of patients with MDD and 97 healthy controls performed a face-matching task during functional magnetic resonance imaging. We used dynamic causal modeling to estimate task-dependent effective connectivity at the subject level. Parametric empirical Bayes was performed to quantify group differences in effective connectivity.

MDD patients showed decreased effective connectivity from the left amygdala and left lateral prefrontal cortex to the fusiform gyrus compared to relatives and controls, whereas patients and relatives showed decreased connectivity from the right orbitofrontal cortex to the left insula and from the left orbitofrontal cortex to the right fusiform gyrus compared to controls. Relatives showed increased connectivity from the anterior cingulate cortex to the left dorsolateral prefrontal cortex compared to patients and controls.

Our results suggest that the depressive state alters top-down control of higher visual regions during face processing. Alterations in connectivity within the cognitive control network present potential risk or resilience mechanisms.

Extensive research has shown abnormal cerebral blood flow (CBF) in patients with major depressive disorder (MDD) that is a heritable disease. The objective of this study was to investigate the genetic mechanisms of CBF abnormalities in MDD.

To achieve a more thorough characterization of CBF changes in MDD, we performed a comprehensive neuroimaging meta-analysis of previous literature as well as examined group CBF differences in an independent sample of 133 MDD patients and 133 controls. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were conducted to identify genes whose expression correlated with CBF changes in MDD, followed by a set of gene functional feature analyses.

We found increased CBF in the reward circuitry and default-mode network and decreased CBF in the visual system in MDD patients. Moreover, these CBF changes were spatially associated with expression of 1532 genes, which were enriched for important molecular functions, biological processes, and cellular components of the cerebral cortex as well as several common mental disorders. Concurrently, these genes were specifically expressed in the brain tissue, in immune cells and neurons, and during nearly all developmental stages. Regarding behavioral relevance, these genes were associated with domains involving emotion and sensation. In addition, these genes could construct a protein-protein interaction network supported by 60 putative hub genes with functional significance.

Our findings suggest a cerebral perfusion redistribution in MDD, which may be a consequence of complex interactions of a wide range of genes with diverse functional features.

Psychological models of posttraumatic stress disorder (PTSD) and prolonged grief disorder (PGD) make predictions about the role of unhelpful coping strategies in maintaining difficulties by blocking self-correction of negative appraisals and memory integration following stressful life events like bereavement. However, few studies have tested these predictions directly.

We used counterfactually based causal mediation to assess whether unhelpful coping strategies mediated the relationship between (1) loss-related memory characteristics and/or (2) negative grief-related appraisals and symptoms of PGD, PTSD and depression using a three-wave longitudinal sample (N = 275). Appraisals and memory characteristics were measured at time point 1, unhelpful coping strategies at T2, and symptom variables at T3. Additionally, multiple mediation analyses within a structural equation modelling (SEM) framework assessed which types of coping strategies differentially mediated symptoms of PGD, PTSD and depression.

Coping strategies mediated the relationship between negative appraisals and memory characteristics and symptoms of PGD, PTSD and depression after adjusting for demographics and loss characteristics. Sensitivity analyses suggested that these results were most robust for PGD, followed by PTSD and then depression. Multiple mediation analyses suggested that all four subscales (avoidance, proximity seeking, loss rumination and injustice rumination) individually mediated the effect of memory characteristics and appraisals on PGD.

These results suggest that core predictions of the cognitive model for PTSD and the cognitive behavioural model of PGD are useful in predicting symptoms of post-loss mental health problems in the first 12–18 months after loss. Targeting unhelpful coping strategies is likely to reduce symptoms of PGD, PTSD and depression.

While suicide rates have recently declined for White individuals, rates among Black and Hispanic individuals have increased. Yet, little is known about racial/ethnic differences in precursors to suicide, including suicidal ideation (SI) and suicide attempts (SA).

Data from 2009–2020 National Survey of Drug Use and Health (NSDUH) consisted of non-institutionalized US civilians aged ⩾18 (n = 426 008). We compared proportions of White, Black, and Hispanics among adults reporting no past-year suicidal thoughts/behavior, SI, and SA. Multivariable-adjusted analyses were used to evaluate the independence of observed racial/ethnic differences in past-year SI, SA, and mental health service use.

In the entire sample, 20 791 (4.9%) reported past-year SI only and 3661 (0.9%) reported a SA. Compared to White individuals, Black and Hispanic individuals were significantly less likely to report past-year SI [OR 0.73 (95% CI 0.69–0.77); OR 0.75 (95% CI 0.71–0.79), respectively], but more likely to report a past-year SA [OR 1.45 (95% CI 1.28–1.64); OR 1.19 (95% CI 1.04–1.37), respectively] even after multivariable adjustment. Black and Hispanic individuals were significantly less likely to use mental health services, but the lack of significant interactions between race/ethnicity and SI/SA in association with service use suggests differences in service use do not account for differences in SI or SA.

Black and Hispanic individuals are significantly less likely than White individuals to report SI but more likely to report SAs, suggesting differences in suicidal behavior across race/ethnicity that may be impacted by socio-culturally acceptable expressions of distress and structural racism in the healthcare system.

Studies investigating cognitive impairments in psychosis and depression have typically compared the average performance of the clinical group against healthy controls (HC), and do not report on the actual prevalence of cognitive impairments or strengths within these clinical groups. This information is essential so that clinical services can provide adequate resources to supporting cognitive functioning. Thus, we investigated this prevalence in individuals in the early course of psychosis or depression.

A comprehensive cognitive test battery comprising 12 tests was completed by 1286 individuals aged 15–41 (mean age 25.07, s.d. 5.88) from the PRONIA study at baseline: HC (N = 454), clinical high risk for psychosis (CHR; N = 270), recent-onset depression (ROD; N = 267), and recent-onset psychosis (ROP; N = 295). Z-scores were calculated to estimate the prevalence of moderate or severe deficits or strengths (>2 s.d. or 1–2 s.d. below or above HC, respectively) for each cognitive test.

Impairment in at least two cognitive tests was as follows: ROP (88.3% moderately, 45.1% severely impaired), CHR (71.2% moderately, 22.4% severely impaired), ROD (61.6% moderately, 16.2% severely impaired). Across clinical groups, impairments were most prevalent in tests of working memory, processing speed, and verbal learning. Above average performance (>1 s.d.) in at least two tests was present for 40.5% ROD, 36.1% CHR, 16.1% ROP, and was >2 SDs in 1.8% ROD, 1.4% CHR, and 0% ROP.

These findings suggest that interventions should be tailored to the individual, with working memory, processing speed, and verbal learning likely to be important transdiagnostic targets.

Symptoms of attention deficit hyperactivity disorder (ADHD) and trait impulsivity have been associated with disordered eating but are seldom assessed in community studies, or longitudinally and little is known about the mediating mechanisms.

We tested associations between ADHD symptoms and disordered eating cross-sectionally and between trait impulsivity and disordered eating longitudinally. We utilised data from a normative cohort of young adults (642 participants: 65% female, Mage = 23 years). Participants were classified as high risk or low risk for disordered eating using the SCOFF instrument. In the first two steps of both cross-sectional and longitudinal hierarchical logistic regression models, demographics and covariates were entered. For the cross-sectional regression, Adult ADHD self-report scale (ASRS) scores, separated into inattentive and hyperactive/impulsive symptoms, were entered in the third step. In a separate longitudinal model, Barratt impulsivity scale subscales (attentional, motor and non-planning impulsivity) were entered in the third step. Depression, as assessed by the moods and feelings questionnaire (MFQ), was examined as a mediator.

Cross-sectionally, sex, MFQ score and inattentive symptoms predicted disordered eating risk (model R2 = 20%). Longitudinally, sex, MFQ score and attentional impulsivity predicted disordered eating risk (model R2 = 16%). The relationship between inattentive symptoms and the disordered eating risk was partially mediated by MFQ score, whereas the relationship between attentional impulsivity and the disordered eating risk was fully mediated by MFQ scores.

These data highlight (1) a specific role for inattentive symptoms of ADHD and (2) the importance of both depression and impulsivity in predicting eating disorder risk.

Previous studies have demonstrated substantial associations between substance use disorders (SUD) and suicidal behavior. The current study empirically assesses the extent to which shared genetic and/or environmental factors contribute to associations between alcohol use disorders (AUD) or drug use disorders (DUD) and suicidal behavior, including attempts and death.

The authors used Swedish national registry data, including medical, pharmacy, criminal, and death registrations, for a large cohort of twins, full siblings, and half siblings (N = 1 314 990) born 1960–1980 and followed through 2017. They conducted twin-sibling modeling of suicide attempt (SA) or suicide death (SD) with AUD and DUD to estimate genetic and environmental correlations between outcomes. Analyses were stratified by sex.

Genetic correlations between SA and SUD ranged from rA = 0.60–0.88; corresponding shared environmental correlations were rC = 0.42–0.89 but accounted for little overall variance; and unique environmental correlations were rE = 0.42–0.57. When replacing attempt with SD, genetic and shared environmental correlations with AUD and DUD were comparable (rA = 0.48–0.72, rC = 0.92–1.00), but were attenuated for unique environmental factors (rE = −0.01 to 0.31).

These findings indicate that shared genetic and unique environmental factors contribute to comorbidity of suicidal behavior and SUD, in conjunction with previously reported causal associations. Thus, each outcome should be considered an indicator of risk for the others. Opportunities for joint prevention and intervention, while limited by the polygenic nature of these outcomes, may be feasible considering moderate environmental correlations between SA and SUD.

The current study examined if early adversity was associated with accelerated biological aging, and if effects were mediated by the timing of puberty.

In early mid-life, 187 Black and 198 White (Mage = 39.4, s.d.age = 1.2) women reported on early abuse and age at first menstruation (menarche). Women provided saliva and blood to assess epigenetic aging, telomere length, and C-reactive protein. Using structural equation modeling, we created a latent variable of biological aging using epigenetic aging, telomere length, and C-reactive protein as indicators, and a latent variable of early abuse using indicators of abuse/threat events before age 13, physical abuse, and sexual abuse. We estimated the indirect effects of early abuse and of race on accelerated aging through age at menarche. Race was used as a proxy for adversity in the form of systemic racism.

There was an indirect effect of early adversity on accelerated aging through age at menarche (b = 0.19, 95% CI 0.03–0.44), in that women who experienced more adversity were younger at menarche, which was associated with greater accelerated aging. There was also an indirect effect of race on accelerated aging through age at menarche (b = 0.25, 95% CI 0.04–0.52), in that Black women were younger at menarche, which led to greater accelerated aging.

Early abuse and being Black in the USA may both induce a phenotype of accelerated aging. Early adversity may begin to accelerate aging during childhood, in the form of early pubertal timing.

The prevention of depression is a key public health policy priority. PredictD is the first risk algorithm for the prediction of the onset of major depression. Our aim in this study was to model the cost-effectiveness of PredictD in depression prevention in general practice (GP).

A decision analytical model was developed to determine the cost-effectiveness of two approaches, each of which was compared to treatment as usual (TAU) over 12 months: (1) the PredictD risk algorithm plus a low-intensity depression prevention programme; and (2) a universal prevention programme in which there was no initial identification of those at risk. The model simulates the incidence of depression and disease progression over 12 months and calculates the net monetary benefit (NMB) from the National Health Service (NHS) perspective.

Providing patients with PredictD and a depression prevention programme prevented 15 (17%) cases of depression in a cohort of 1000 patients over 12 months and had the highest probability of being the optimal choice at a willingness to pay (WTP) of £20 000 for a quality-adjusted life year (QALY). Universal prevention was strongly dominated by PredictD plus a depression prevention programme in that universal prevention resulted in less QALYs than PredictD plus prevention for a greater cost.

Using PredictD to identify primary-care patients at high risk of depression and providing them with a low-intensity prevention programme is potentially cost-effective at a WTP of £20 000 per QALY.

Co-morbidity among use of different substances can be explained by a shared underlying dimensional factor. What remains unknown is whether the relationship between substance use and various co-morbid mental disorders can be explained solely by the general factor or whether there remain unique contributions of specific substances.

Data were from the 2007 Australian National Survey of Mental Health and Wellbeing (NSMHWB). A unidimensional latent factor was constructed that represented general substance use. The shared and specific relationships between lifetime substance use indicators and internalizing disorders, suicidality and psychotic-like experiences (PLEs) were examined using Multiple Indicators Multiple Causes (MIMIC) models in the total sample. Additional analyses then examined the shared and specific relationships associated with substance dependence diagnoses as indicators of the latent trait focusing on a subsample of substance users.

General levels of latent substance use were significantly and positively related to internalizing disorders, suicidality and psychotic-like experiences. Similar results were found when examining general levels of latent substance dependence in a sample of substance users. There were several direct effects between specific substance use/dependence indicators and the mental health correlates that significantly improved the overall model fit but they were small in magnitude and had relatively little impact on the general relationship.

The majority of pairwise co-morbid relationships between substance use/dependence and mental health correlates can be explained through a general latent factor. Researchers should focus on investigating the commonalities across all substance use and dependence indicators when studying mental health co-morbidity.

This is the first report on the association between trauma exposure and depression from the Advancing Understanding of RecOvery afteR traumA(AURORA) multisite longitudinal study of adverse post-traumatic neuropsychiatric sequelae (APNS) among participants seeking emergency department (ED) treatment in the aftermath of a traumatic life experience.

We focus on participants presenting at EDs after a motor vehicle collision (MVC), which characterizes most AURORA participants, and examine associations of participant socio-demographics and MVC characteristics with 8-week depression as mediated through peritraumatic symptoms and 2-week depression.

Eight-week depression prevalence was relatively high (27.8%) and associated with several MVC characteristics (being passenger v. driver; injuries to other people). Peritraumatic distress was associated with 2-week but not 8-week depression. Most of these associations held when controlling for peritraumatic symptoms and, to a lesser degree, depressive symptoms at 2-weeks post-trauma.

These observations, coupled with substantial variation in the relative strength of the mediating pathways across predictors, raises the possibility of diverse and potentially complex underlying biological and psychological processes that remain to be elucidated in more in-depth analyses of the rich and evolving AURORA database to find new targets for intervention and new tools for risk-based stratification following trauma exposure.

Gambling disorder (GD), recognized in Diagnostic and Statistical Manual of Mental Disorders, Version 5 (DSM-5) as a behavioral addiction, is associated with a range of adverse outcomes. However, there has been little research on the genetic and environmental influences on the development of this disorder. This study reports results from the largest twin study of GD conducted to date.

Replication and combined analyses were based on samples of 3292 (mean age 31.8, born 1972–79) and 4764 (mean age 37.7, born 1964–71) male, female, and unlike-sex twin pairs from the Australian Twin Registry. Univariate biometric twin models estimated the proportion of variation in the latent GD liability that could be attributed to genetic, shared environmental, and unique environmental factors, and whether these differed quantitatively or qualitatively for men and women.

In the replication study, when using a lower GD threshold, there was evidence for significant genetic (60%; 95% confidence interval (CI) 45–76%) and unique environmental (40%; 95% CI 24–56%), but not shared environmental contributions (0%; 95% CI 0–0%) to GD liability; this did not significantly differ from the original study. In the combined analysis, higher GD thresholds (such as one consistent with DSM-5 GD) and a multiple threshold definitions of GD yielded similar results. There was no evidence for quantitative or qualitative sex differences in the liability for GD.

Twin studies of GD are few in number but they tell a remarkably similar story: substantial genetic and unique environmental influences, with no evidence for shared environmental contributions or sex differences in GD liability.

Recent neurodevelopmental models of schizophrenia, together with substantial evidence of neurocognitive dysfunction among people with schizophrenia, have led to a widespread view that general cognitive deficits are a central aspect of schizophrenic pathology. However, the temporal relationships between intellectual functioning and schizophrenia-spectrum illness remain unclear.

Longitudinal data from the Copenhagen High-Risk Project (CHRP) were used to evaluate the importance of intellectual functioning in the prediction of diagnostic and functional outcomes associated with the schizophrenia spectrum. The effect of spectrum illness on intellectual and educational performance was also evaluated. The sample consisted of 311 Danish participants: 99 at low risk, 155 at high risk, and 57 at super-high risk for schizophrenia. Participants were given intellectual [Weschler's Intelligence Scale for Children (WISC)/Weschler's Adult Intelligence Scale (WAIS)] assessments at mean ages of 15 and 24 years, and diagnostic and functional assessments at mean ages 24 and 42 years.

Intellectual functioning was found to have no predictive relationship to later psychosis or spectrum personality, and minimal to no direct relationship to later measures of work/independent living, psychiatric treatment, and overall severity. No decline in intellectual functioning was associated with either psychosis or spectrum personality.

These largely negative findings are discussed in the light of strong predictive relationships existing between genetic risk, diagnosis and functional outcomes. The pattern of predictive relationships suggests that overall cognitive functioning may play less of a role in schizophrenia-spectrum pathology than is widely believed, at least among populations with an evident family history of schizophrenia.

The outbreak of COVID-19 generated severe emotional reactions, and restricted mobility was a crucial measure to reduce the spread of the virus. This study describes the changes in public emotional reactions and mobility patterns in the Chinese population during the COVID-19 outbreak.

We collected data on public emotional reactions in response to the outbreak through Weibo, the Chinese Twitter, between 1st January and 31st March 2020. Using anonymized location-tracking information, we analyzed the daily mobility patterns of approximately 90% of Sichuan residents.

There were three distinct phases of the emotional and behavioral reactions to the COVID-19 outbreak. The alarm phase (19th–26th January) was a restriction-free period, characterized by few new daily cases, but a large amount public negative emotions [the number of negative comments per Weibo post increased by 246.9 per day, 95% confidence interval (CI) 122.5–371.3], and a substantial increase in self-limiting mobility (from 45.6% to 54.5%, changing by 1.5% per day, 95% CI 0.7%–2.3%). The epidemic phase (27th January–15th February) exhibited rapidly increasing numbers of new daily cases, decreasing expression of negative emotions (a decrease of 27.3 negative comments per post per day, 95% CI −40.4 to −14.2), and a stabilized level of self-limiting mobility. The relief phase (16th February–31st March) had a steady decline in new daily cases and decreasing levels of negative emotion and self-limiting mobility.

During the COVID-19 outbreak in China, the public's emotional reaction was strongest before the actual peak of the outbreak and declined thereafter. The change in human mobility patterns occurred before the implementation of restriction orders, suggesting a possible link between emotion and behavior.