Current bipolar disorder (BD) therapies suffer from limited efficacy and adverse effects, necessitating mechanistically grounded targets.

We integrated BD genome-wide association study data (158,036 cases; 2,796,499 controls) with brain proteomics (ROSMAP and Banner dorsolateral prefrontal cortex, n = 376 and 152) to perform proteome-wide association studies (PWAS). Bayesian colocalization and summary-data-based Mendelian randomization (SMR) prioritized causal genes. Cell-type-specific transcriptomics validated dysregulation in iPSC-derived neurons, astrocytes, and postmortem hippocampus/prefrontal cortex. Weighted gene co-expression networks (WGCNAs), functional enrichment, and molecular docking assessed functional pathways and druggability.

PWAS identified eight BD-associated genes (false discovery rate < 0.05), with DOC2A emerging as the top candidate. Colocalization (H4 > 0.8) and SMR supported a causal association of DOC2A with BD, with no pleiotropy (heterogeneity in dependent instruments P > 0.01); DOC2A expression decreased in BD across neurons (P = 4.26 × 10−2), astrocytes (P = 2.09 × 10−2), hippocampus (P = 9.80 × 10−3, t = −2.738), and prefrontal cortex (P = 1.44 × 10−2, t = −2.580); WGCNA positioned DOC2A as a key regulator (module membership/gene significance P < 0.05) of co-expression networks enriched for BD-associated processes including neurotransmitter secretion and postsynaptic actin cytoskeleton organization (P < 0.05); molecular docking revealed favorable-affinity binding (ΔG < −4 kcal/mol) between DOC2A and BD-related drugs and neuroprotective compounds.

Our convergent multi-omics framework highlights DOC2A dysregulation as a key contributor to synaptic dysfunction in BD and nominates it as a promising therapeutic target. The demonstrated interaction with existing neuroactive compounds provides immediate translational avenues.

Maternal mental health strongly influences child development and depression risk. This study investigated how positive and negative dimensions of prenatal maternal mental health differentially shape childhood depressive symptoms through cognitive mediators.

Participants were drawn from the Growing Up in Singapore Towards Healthy Outcomes (GUSTO) cohort. Of the 1198 mother–child dyads enrolled, 523 (52.6% boys) had sufficient data for the mediation analysis. Maternal mental health at 26 weeks’ gestation was assessed using a bifactor model derived from the Beck Depression Inventory-II, State–Trait Anxiety Inventory, and Edinburgh Postnatal Depression Scale. Child language ability was measured at age 2 years with the Bayley Scales of Infant Development, executive function at age 7 years with the Behaviour Rating Inventory of Executive Function, and depressive symptoms at age 9 years with the Children’s Depression Inventory-2. Serial mediation models tested hypothesized pathways.

Distinct mediation pathways emerged. Positive maternal mental health was associated with enhanced early language ability, which in turn was associated with fewer depressive symptoms in later childhood (β = −0.017, 95% CI: −0.042, −0.003). Conversely, negative maternal mental health was associated with poorer executive functioning, which in turn was associated with more depressive symptoms (β = 0.040, 95% CI: 0.016–0.077).

Positive and negative maternal mental health are linked to childhood depressive symptoms through distinct neurocognitive pathways. By identifying language and executive function as specific developmental mediators, our findings point to targeted and developmentally sensitive intervention opportunities to disrupt intergenerational pathways of depression.

The high comorbidity between mental and cardiovascular diseases is widely recognized, but the underlying mechanisms are not yet well understood. We investigated the familial coaggregation and shared genetic loading between these diseases.

Using claims data from Taiwan’s universal health insurance program, we identified cohorts of 4,513,509 individuals with parental information and 3,330,181 with full-sibling information born between 1970 and 1999, and followed up until 2020. Genotyping was available for 106,796 unrelated participants from the Taiwan Biobank. Multiple logistic regression models were used to estimate the association of parental history, full-sibling history, and polygenic risk scores (PRSs) for severe mental illnesses (schizophrenia, bipolar disorder, major depressive disorder [MDD]) with the risk of myocardial infarction, stroke, peripheral arterial disease (PAD), and heart failure.

Individuals with a parental history of schizophrenia, bipolar disorder, or MDD were more likely to have stroke and PAD. Coaggregation in full-siblings was observed for MDD with myocardial infarction and heart failure, bipolar disorders with stroke, and schizophrenia with PAD. The PAD risk increased with more relatives affected by MDD; the magnitude of association was larger when both parents were affected than when either parent was affected, and when there were two affected siblings than in those with only one. MDD PRS was positively associated with the risk of myocardial infarction and PAD.

This study revealed familial coaggregation between mental and cardiovascular diseases, and shared polygenic liability of MDD with cardiovascular diseases. Our findings suggest the potential benefit of family-based integrated screening and preventive strategies.

Sub-threshold depression (SD) affects around 11% of adolescents and can be as impairing as conditions reaching the full diagnostic criteria of Major Depressive Disorder (MDD). However, limited research has been conducted on how affective disturbances manifest in SD during adolescence, a period of affective vulnerability. We compared three groups of adolescents along the spectrum of depression on their positive affective (PA) and negative affective (NA) levels and dynamics, including variability, inertia, and reactivity to event-related stress and pleasure in daily life.

One hundred and ninety eight adolescents (age 12–18), grouped by psychiatric diagnosis (MDD = 66; SD = 35; healthy controls, HC = 88), completed a 14-day experience sampling on their smartphone, clinical ratings, and questionnaires. They were recruited from multiple sources, including an epidemiologic study and specialist clinics.

The level of NA was the highest in MDD, followed by SD and HC; vice versa for PA. MDD and SD displayed greater NA variability than HC. NA inertia was greater in MDD than SD and HC. NA reactivity (to event-related pleasure and stress) and PA reactivity (to event-related pleasure) were greater in MDD and SD than HC. SD showed greater PA reactivity to event-related stress than MDD.

Adolescents with SD were as reactive and expansive in their NA experience as the MDD group, but they did not stay in that negative state for as long. The SD group was more reactive than HC to event-related pleasure and stress, suggesting heightened sensitivity. Clinical implications of emotional sensitivity and flexibility on early intervention for depression are discussed.

Dialectical behavior therapy skills training (DBT-ST) has received empirical evidence for treating non-suicidal self-injury (NSSI). However, its effectiveness in Chinese contexts remains understudied. This study aims to explore the effectiveness of DBT-ST for NSSI in a clinical sample of individuals with NSSI.

We conducted a multicenter, randomized clinical trial in China to evaluate the effectiveness of a 13-week DBT-ST compared with social support group therapy (SSGT). A total of 196 individuals with mental disorders and NSSI were recruited. The primary outcome was the frequency of NSSI thoughts and behaviors, assessed using the Ottawa Self-Injury Inventory.

Participants were randomized to the DBT-ST group (n = 97) or the SSGT group (n = 99). DBT-ST was significantly more effective than SSGT in reducing the frequency of NSSI behaviors. It also showed superior effects on borderline symptoms and multiple domains of psychological functioning, including emotion dysregulation, impulsivity, alexithymia, mindfulness, psychological resilience, and emotional intelligence. Both groups exhibited significant reductions in the frequency of NSSI thoughts, suicidal ideation and attempts, and depression, with no significant between-group differences in these outcomes.

These findings confirm that the 13-week DBT-ST intervention is an effective treatment for Chinese patients with NSSI in clinical settings.

This real-world study aimed to characterize patients with schizophrenia who achieve sustained good functional outcomes after antipsychotic discontinuation and to develop the Functional Remission in Schizophrenia after Antipsychotic Discontinuation (FURSAD) predictive model.

We retrospectively identified individuals aged 18–65 years with schizophrenia (ICD-10) from the Shanghai Mental Health Center discharge database. Patients who discontinued antipsychotics for ≥1 year were classified as functional remission (FR) or functional non-remission (FNR) based on functioning assessments. Sociodemographic, clinical, and treatment-related data were extracted blindly from hospital records and structured interviews.

Among 4,166 discharged patients screened, 180 met the inclusion criteria (FR: 116; FNR: 64). Six independent predictors were identified: total disease course, Clinical Global Impression-Severity (CGI-S) score, Positive and Negative Syndrome Scale (PANSS) emotional distress subscale score, use of first-generation antipsychotics, discontinuation due to treatment benefits, and discontinuation due to lack of insight. The logistic regression model showed strong predictive performance (AUC = 0.867, 95% CI 0.813–0.921), with 82.8% sensitivity and 81.9% specificity. Internal validation was performed via 10-fold cross-validation.

Discontinuation motives and illness trajectory are relevant in predicting long-term functional outcomes. A limitation is that a substantial number of patients could not be recontacted or declined participation, which may introduce selection bias. The FURSAD nomogram may help clinicians estimate the probability of FR 4.5 years post-antipsychotic discontinuation in patients previously on antipsychotics for ≥3 years.

Autistic traits have been associated with greater risk of childhood trauma and adulthood psychopathology. However, the role that childhood trauma plays in the association among autism, autistic traits, and depression in adulthood is poorly understood.

We used a UK-based birth cohort with genotype and phenotype data on autism, autistic traits, childhood trauma, and depression in up to 9,659 individuals prospectively followed up until age 28 years. Using mixed-effects growth-curve models, we assessed trajectories of depression symptoms over time according to autism diagnosis, autism polygenic score and trait measures, and explored whether these differed by trauma exposure. We further investigated the association between autism/autistic traits and depression in adulthood using confounder-adjusted logistic regression models and undertook mediation analyses to investigate the relationship with childhood trauma.

All autism variables demonstrated increased depressive symptom trajectories between ages 10 and 28 years. Social communication difficulties (SCDs) were most strongly associated with a depression diagnosis in adulthood (age 24 OR = 1.86; 95% CIs: 1.15–3.01). Trauma and autistic traits combined to further increase depression symptom scores. Mediation analyses provided evidence for direct pathways between autistic traits and increased risk of depression alongside indirect pathways through increased risk of trauma.

Autism/autistic traits increase the odds of experiencing childhood trauma and of being diagnosed with depression at ages 18 and 24. Depressive symptom trajectories emergent in childhood persist into adulthood. The combined effect of SCDs and childhood trauma is greater than the individual exposures, suggesting worse depression symptomatology following trauma in individuals with SCDs.

Child abuse and low parental affection are established risk factors for higher adulthood panic disorder (PD) severity, but their plausible sleep mediators are under-investigated. We thus examined how actigraphy indices mediated the links between child parental abuse and affection deficits to adulthood PD severity.

Community-dwelling adult participants (N = 1,054) completed a series of self-reports on child parental abuse and affection at Wave 1. An eight-day actigraphy protocol was conducted at Wave 2, 9 years later. Telephone-administered clinical interviews assessing PD symptoms were conducted in W1 and Wave 3, separated by 18 years. A series of bias-corrected, bootstrapped causal mediation analyses was performed.

Paternal, but not maternal abuse, predicted higher rest- and sleep-stage actigraphy markers after 9 years (βs = 0.263–469.79, p < .001), comprising more activity counts, longer wake time, higher wake time percentage, and wake bouts. These markers, thereby, mediated the trajectory from paternal abuse to higher PD severity (average causal mediation effects (ACMEs): βs = 0.003–0.020, 95% CIs excluding zero, p < .001). Likewise, paternal affection deficits predicted greater disturbances in rest- and sleep-stage actigraphy (all p < .05), thereby mediating the link to greater PD severity (ACMEs: βs = 0.001–0.002, p ≤ .04). Neither maternal abuse nor affection was a significant mediator.

These outcomes aligned with, but do not verify, a causal mediation argument wherein actigraphy-derived nocturnal sleep–wake disturbances partially accounted for the trajectory from adverse paternal caregiving encounters to adulthood PD severity. Strategically targeting sleep disturbances may reflect a viable intervention approach for persons with past child paternal abuse learning histories.

Psychotic-like experiences (PLEs) are common in adolescence and often associated with later mental health difficulties. Although many psychosocial factors are related to PLEs, little is known about how these factors interact over time. Longitudinal network analysis allows examination of the stability of symptom associations and identification of potential intervention targets. This study investigated the structure and temporal stability of PLE networks in a large community-based adolescent cohort.

Adolescents aged 13–19 years (N = 605 with complete data across all time points) completed assessments at baseline, 12 months, and 24 months. Measures included positive and negative PLEs, cognitive biases, depression, anxiety, trauma, and interpersonal sensitivity. Networks were estimated at each time point, and permutation-based tests were used to compare network structure and overall connectivity across time. Centrality stability was assessed using bootstrapping procedures.

Network structures were stable across the 2-year period, with no significant differences in overall organization or connectivity between time points. Depression consistently showed the highest centrality, followed by anxiety and attributional bias. Positive PLEs were most strongly associated with anxiety, while negative PLEs showed their strongest associations with depression. Attributional bias remained centrally positioned and was strongly linked to trauma. All networks showed robust accuracy and high stability.

Despite considerable developmental change during adolescence, the psychosocial architecture of PLEs remained notably stable. Depression, anxiety, and attributional biases emerged as consistent key nodes, highlighting them as promising targets for prevention and early intervention in adolescents at risk for persistent PLEs.

Individuals with high trait anxiety (HA) exhibit maladaptive goal-directed behaviors, which are associated with dysfunctional counterfactual-thinking during decision-making. While lesion studies suggest the causal role of the ventromedial prefrontal cortex (vmPFC) in counterfactual-thinking, its modulatory role in anxiety-related counterfactual decision-making remains uncharacterized. Here, we bridge this gap by examining the characteristics of decision-making (forward counterfactual) and emotion responses (backward counterfactual) in trait anxiety, as well as its underlying modulatory mechanisms by targeting at the vmPFC.

A counterfactual-thinking paradigm was employed to identify the patterns of goal-directed choice and emotional responses in trait anxiety in experiment 1. In all, 107 participants with varied levels of trait anxiety were recruited and counterfactual indices were modeled. In experiment 2, the high-definition transcranial direct current stimulation (HD-tDCS) was applied to modulate forward and backward counterfactual responses targeting at the vmPFC in HA. Based on the exploratory results of experiment 1, 61 participants with HA were randomly assigned to cathodal or sham stimulation.

High level of anxiety was associated with stronger emotional responses to backward counterfactuals, more anticipations of regret to forward counterfactuals, higher value-expectations to potential rewards, and more risk-taking behaviors. Related to sham, cathodal HD-tDCS over the vmPFC in HA showed normalized sensitivity to anticipated regret, which leads to less risk-taking behaviors during goal-directed decision-making.

The findings provide evidences of disrupted forward and backward counterfactual processing in anxious individuals, wherein the vmPFC plays a modulatory role. Targeting vmPFC with noninvasive stimulation may normalize maladaptive decision patterns in anxiety and anxiety disorders.

Persons with substance use disorders (SUD) often suffer from additional comorbidities. Researchers have explored this overlap via phenome-wide association studies (PheWASs). However, PheWASs are largely cross-sectional, limiting our understanding of whether diagnoses predate the development of an SUD. We characterize whether polygenic scores (PGSs) are associated with time to comorbid diagnoses in electronic health records (EHR) after the first documented SUD diagnosis.

Using data from All of Us (N = 393,596), we explored: (1) whether social determinants of health (SDoHs) are associated with lifetime risk of SUD (N cases = 42,568) and (2) within a subset those with a diagnosed SUD and available genetic data SUD (N = 21,357), whether PGS for alcohol use disorders, cannabis use disorders, depression, externalizing, posttraumatic stress disorder, and schizophrenia were associated with subsequent diagnoses via a phenome-wide survival analysis.

Multiple SDoHs were associated with lifetime SUD diagnosis, with annual household income having the largest overall associations (e.g. <$10 K annually vs $100 K–$150 K annually: OR = 4.18; 95% CI = 3.92, 4.45). There were 86 phenome-wide significant PGS associations with subsequent diagnoses across various bodily systems. PGSs for alcohol use disorders, posttraumatic stress disorder, and schizophrenia were each associated with time to their respective diagnoses.

Social determinants, especially those related to income, have profound associations with lifetime SUD risk. Additionally, PGSs for psychiatric conditions are associated with multiple post-SUD diagnoses within those with a SUD, suggesting PGS may capture information beyond lifetime risk, including timing and severity of comorbidities related to SUD.

Inhibitory control deficits represent a core cognitive feature in patients with obsessive-compulsive disorder (OCD), yet their neurophysiological mechanisms remain unclear. Electroencephalogram (EEG) microstates offer a novel framework for investigating large-scale brain network dynamics in psychiatric disorders. This cross-sectional study aimed to investigate EEG microstate dynamics in OCD patients and their relationships with cognitive and response inhibition.

A total of 91 OCD patients and 76 healthy controls were recruited. Participants completed an Emotional Stroop Task (EST) and a stop-signal task (SST). Resting-state EEG was recorded, and microstate parameters and transition probabilities were analyzed. Correlations between microstate parameters and inhibitory control performance were assessed.

OCD patients exhibited significant deficits in both response inhibition and cognitive inhibition, with both types of deficits positively correlated with obsessive symptom severity. Microstate analysis revealed increased mean duration and time coverage of microstate A, but decreased mean duration, occurrence, and coverage of microstate C in OCD patients. Additionally, transition probabilities from microstates B and D to C were significantly elevated. Notably, the mean duration of microstate C was positively correlated with stop-signal reaction time (SSRT), while the occurrence of microstates C and D and the time coverage of microstate D were negatively correlated with the Stroop effect.

These findings reveal dissociable microstate mechanisms associated with distinct inhibitory dysfunction domains in OCD patients. Resting-state microstate dynamics may represent candidate neurobiological markers for cognitive subtype classification in OCD and may help inform the development of targeted therapeutic interventions.

Glymphatic functioning is implicated in cognitive and affective functioning. Given that rumination, a major risk factor for major depressive disorder (MDD), is a cognitive process regulating information processing, knowledge of the neurobiological mechanisms underpinning the relationship among glymphatic functioning, rumination, and depression would offer significant insight into the precipitating and maintenance mechanisms of MDD.

This study recruited 53 MDD patients and 47 matched healthy controls (HCs). Diffusion Tensor Image Analysis along the Perivascular Space (DTI-ALPS) index was computed as a proxy of the glymphatic functioning. Rumination and depressive severity were evaluated using Ruminative Response Scale (RRS) and Hamilton Depression Rating Scale (HAMD), respectively. Static and dynamic functional connectivity (FC/dFC) analyses were performed, and associations with neurotransmitter maps were explored.

MDD patients showed reduced glymphatic function compared to HCs, with lower glymphatic function correlating with more severe depression and rumination. Rumination mediated the glymphatic–depression relationship. Furthermore, overlapping static FC involving default mode and subcortical networks linked the glymphatic functioning and rumination. Edge-centric dynamic FC analysis showed reduced State 3 occurrence and heightened rumination, further mediating the glymphatic–rumination relationship in HCs. Both FC biomarkers spatially correlated with various neurotransmitter maps (e.g. dopamine).

Glymphatic dysfunction may exacerbate depression by disrupting brain networks and neurotransmitter balance, trapping individuals in maladaptive rumination. Enhancing glymphatic flow (e.g. via physical exercise) could restore neurobiological health, breaking the maladaptive cycles. This highlights glymphatic functioning as a potential therapeutic target bridging neurobiology, cognition, and depression severity.

Safety behaviors are a common response to persecutory ideation in psychosis. They potentially contribute to the maintenance and exacerbation of symptoms and emotional distress and are therefore a promising treatment target. However, empirical evidence for this hypothesized maintenance role is scarce. We therefore examined cross-sectional and micro-longitudinal associations between safety behaviors, negative affect, and persecutory ideation in the daily lives of individuals with psychotic disorders.

We assessed safety behaviors, persecutory ideation, and negative affect at baseline and 10 times/day during one week of Ecological Momentary Assessment (EMA) in N = 64 participants with persecutory ideation and a psychotic disorder.

At baseline, safety behaviors were positively correlated with persecutory ideation (r = .47), depression (r = .67), and anxiety (r = .69). Safety behaviors assessed at baseline and safety behaviors assessed in daily life showed a moderate correlation (r = .56). Multilevel analyses of the longitudinal EMA data revealed persecutory ideation (β = .16) and negative affect (β = .11) to predict subsequent use of safety behaviors. Momentary use of safety behaviors predicted subsequent persecutory ideation (β = .13) and negative affect (β = .18).

Our results provide evidence for a vicious cycle of maintenance involving persecutory ideation, negative affect, and safety behaviors. Targeting safety behaviors with ecological momentary interventions in daily life could be a promising approach to interrupt this cycle.

White matter (WM) abnormalities are implicated in major depressive disorder (MDD), yet the organization of white matter morphometric similarity networks (WM-MSNs) – which capture interregional similarity in voxel-wise WM morphology – and the transcriptional mechanisms associated with their disruption remain insufficiently understood.

Using T1-weighted MRI from a large multisite sample (1,154 individuals with MDD and 1,026 healthy controls), we constructed individualized WM-MSNs. Group differences were assessed at the edge, global, and nodal levels. To identify molecular pathways underlying these alterations, nodal abnormalities were linked to regional gene expression profiles from the Allen Human Brain Atlas using spatially informed transcriptomic association, followed by functional, cell-type-specific, and developmental enrichment analyses.

MDD showed distributed but selective reorganization of WM-MSNs. Network-based statistics revealed two significant components, with 118 edges exhibiting increased morphometric similarity and 45 showing decreased similarity. Globally, MDD demonstrated higher small-worldness, clustering coefficient, global efficiency, and local efficiency, together with shorter characteristic path length. Nodal disruptions were concentrated in major commissural and association tracts – including the corpus callosum, cingulum, uncinate fasciculus, and tapetum. Transcriptomic integration indicated enrichment for gene signatures related to oligodendrocyte function, myelination, lipid metabolism, axonal organization, and cellular stress-related molecular processes, with implicated genes showing broad developmental-stage expression.

MDD is associated with robust alterations in individualized WM-MSNs that converge with transcriptional signatures linked to myelination, metabolic processes, axonal structure, and cellular stress, linking macroscale network disruption to underlying molecular architecture and providing cross-scale insights into WM pathology in depression.

Cognitive impairment is a common and persistent feature of depression, yet it remains poorly understood and inadequately treated. Preclinical and human studies suggest that stimulating 5-HT4 receptors (5-HT4R) enhances neuroplasticity and improves cognition. This novel study examines the cognitive effects of 5-HT4R agonism in adults with a history of recurrent depression.

Fifty participants who were not currently depressed but had experienced at least two previous episodes of depression were randomized in a double-blind design either to prucalopride (2 mg daily, titrated from 1 mg) or to placebo for 7–10 days. Participants completed self-report questionnaires and a task battery at baseline and post-intervention assessing declarative memory, working memory, emotional processing, and executive function.

Compared to placebo, prucalopride significantly improved word recall on an auditory verbal learning task and was associated with faster response times on a complex working memory task without loss of accuracy. It also improved the accurate recognition of rapidly presented facial expressions. Composite analysis of non-emotional tasks identified that the prucalopride group participants post-intervention were faster and more accurate than at baseline compared to those receiving placebo. Prucalopride had minimal effects on affective cognition, consistent with previous findings. Cognitive improvements were independent of baseline mood symptoms or self-reported cognitive difficulties.

Short-term 5-HT4R agonism improved performance on multiple objective cognitive measures in individuals with remitted depression. These findings replicate our previous results in healthy volunteers showing a pro-cognitive effect of prucalopride and support a role for 5-HT4Rs as a promising target for cognitive enhancement in mood disorders.

The COVID-19 pandemic exposed individuals to numerous psychosocial and health-related stressors associated with adjustment disorder (AjD) symptoms, yet it remains unclear which factors are most predictive.

Using mixed-effects regression random forests (MERF), a machine learning approach that combines random forests with mixed-effects regressions, we analyzed longitudinal data from 15,155 adults across 11 European countries collected at three time points between June 2020 and January 2022. We evaluated 245 candidate predictors, including sociodemographic, pandemic-related, and health-related factors, for their relative importance in predicting AjD symptoms (ADNM-8).

The seven most influential predictors, ranked in descending order of importance, were uncertainty about the pandemic’s duration and risks, poor health, social isolation, conflicts at home, loss of daily structure, fear of infection, and restricted personal contact with close others.

AjD symptoms were most strongly linked to factors related to lack of control (e.g., uncertainty, loss of daily structure, fear of infection), as well as current poor health and reduced social connectedness. Interventions that enhance a sense of control through clear communication, help individuals re-establish daily routines, and strengthen social connectedness may mitigate AjD symptoms during future public health crises. Our findings also highlight the potential of machine learning approaches for identifying complex patterns across high-dimensional predictors of clinical symptoms, which may improve prediction accuracy in mental health research.

Living in a country with a large gap between high and low earners has been linked to poor health, including depression. Less studied is gene-by-environment interplay with income inequality as the environmental exposure. Here, we examine the association between childhood exposure to inequality and individual differences in adult depressive symptoms, testing for moderation of genetic influences by inequality using polygenic indices for major depressive disorder, as well as twin models.

The research participants were 69,924 members of twin studies from four developed countries, born between 1893 and 1979, aged 22–103 years at depressive symptom assessment. Genotyping was available for 6,256 participants. Income inequality was operationalized as share of income accruing to the top 1% for each country when the participants were between age 5 and 15 years.

Childhood income inequality was associated with depressive symptom scores in adulthood, adjusting for covariates. Each 1% rise in inequality was associated with 0.295 higher depressive symptoms (scaled on T-score units). In genetic analyses, interaction effects showed that men who faced more inequality as children and had higher genetic risk for depression reported modestly higher depressive symptoms compared to other men. For women, both genetic risk and inequality mattered, with each independently associated with depressive symptoms. Twin models showed that inequality moderated genetic variance underlying depressive symptoms; heritability of depressive symptoms was higher where exposure to income inequality was higher.

Findings illustrate the long reach of childhood exposure to income inequality and suggest that advantaged environments may help protect against the effects of deleterious genes.