Parenting is related to the development of callous-unemotional (CU) traits (i.e. low empathy and restricted guilt), making it an important target of interventions for childhood conduct problems (CPs). However, the relative importance of different parenting features in relation to the development of CU traits remains unclear. This study used machine learning to examine multiple parenting features assessed across infancy and early childhood as predictors of CU traits and CPs in early adolescence.

Data were from the Family Life Project (N = 1,292; 49% female, 41% Black, and 28% below the poverty line). Seventy-four parenting predictors were assessed at eight time points between children aged 6–90 months using parent-reported questionnaires and observer ratings of videotaped interactions and home visits. CU traits and CPs were assessed via parent-reported questionnaires in preadolescence (12–14 years).

Parenting features explained 8.2% of CU traits variability in preadolescence, with top predictors including early sensitive parenting and later behavior management and scaffolding practices. Prediction of CPs was weaker, with parenting explaining 4.5% of the variability.

Results highlight that disruption in close and sensitive early parent–child relationships is relevant to the development of CU traits. Results from the prediction of CPs indicate a more heterogeneous etiology. Findings support targeting parental sensitivity and behavior management within preventative interventions for CU traits and CPs.

Children with attention-deficit/hyperactivity disorder (ADHD) frequently exhibit impairing emotional dysregulation along with inattention and hyperactivity. We aim to parse the heterogeneity of behavioral and emotional dysregulation in ADHD using latent brain factors based on cortical thickness (CT), and examine associated differences in intrinsic functional connectivity (iFC).

Data were collected from 123 children (39 ADHD, 47 ADHD with impairing emotional outbursts [ADHD + IEO], 37 neurotypical controls [NT], 5–9.9 years old). First, exploratory factor analysis revealed latent behavioral factors. Using Latent Dirichlet allocation, we decomposed heterogeneous CT patterns into parsimonious latent brain factors. We further investigated the functional relevance of brain regions showing structural differences in the ADHD + IEO group and examined associations between brain and behavioral latent factors.

Among the four behavioral factors identified (Externalizing, Emotion Dysregulation, Internalizing, and Surgency/Impulsivity), the dominant factor – Externalizing behavior – significantly differentiated the ADHD + IEO from the ADHD and NT groups. A conjunction analysis of the three brain factors revealed significantly thicker CT in the dorsolateral prefrontal cortex for ADHD + IEO compared to NT. Using this region as a seed, we found reduced functional connectivity primarily in the default mode network, which differentiated ADHD + IEO and ADHD groups. Structural brain and iFC measures showed significant associations with the Externalizing behavior factor.

Parsing the neurobiology underlying the heterogeneous presentation of ADHD requires integrating multiple modalities and analytical methods. This study demonstrates that combining behavioral, structural, and functional data reveals unique neural features associated with behavioral and emotional dysregulation.

Seeking to clarify the parent-offspring transmission of Major Depression (MD) and type I Bipolar Disorder (BD), we examined offspring MD and BD risk in five informative parental pairs: Unaffected x MD, Unaffected x BD, MDxMD, MDxBD and BDxBD.

We identified 289,637 individuals born in Sweden 1970-1990, followed through 2018, from parents with MD and/or BD identified from Swedish medical registers. We quantified the MD→MD, BD→BD, MD→BD and BD→MD parent-offspring transmission and explored effects of parental illness on MD→BD conversions.

The risk for MD was modestly and similarly increased in offspring of Unaffected x MD (HR=1.64) and Unaffected x BD parents (HR=1.53), higher in MDxMD and MDxBD pairings (HRs=2.39 and 2.47) and slightly lower in BDxBD matings (HR=2.29). By contrast, risk for BD was much higher in Unaffected x BD versus Unaffected x MD matings (HRs = 5.59 vs. 1.70), further elevated modestly in MDxBD matings (HR=6.26) and very high in BDxBD matings (HR=13.61). The rate of offspring MD→BD conversions was substantially increased by parental BD but not parental MD. Offspring BD was equally predicted by paternal and maternal affective illness while offspring MD was more strongly predicted by maternal than paternal affective illness.

Examining risk for MD and BD in offspring of different parental mating types of MD and BD is an informative strategy for further clarifying the cross-generational transmission of these two partially related and partially distinct mood disorders.

Irritable bowel syndrome (IBS) commonly co-occurs with psychological distress, including depression and anxiety, but the temporal and bidirectional nature of this relationship remains unclear. Dysregulation of the gut–brain–microbiota axis has been proposed as a shared mechanism.

We conducted two retrospective, population-based cohort studies using Taiwan’s National Health Insurance Research Database (2000–2015). Cohort 1 assessed the risk of incident IBS among patients with newly diagnosed depression or anxiety, while Cohort 2 evaluated the risk of subsequent depression or anxiety among patients with newly diagnosed IBS. Propensity score matching, multivariable Cox regression, and Fine–Gray competing risk models were applied.

IBS was associated with increased risks of depression (adjusted hazard ratio [aHR] = 1.55) and anxiety (aHR = 1.68). Conversely, depression and anxiety were associated with higher risks of developing IBS (aHR = 1.45 and 1.51, respectively). Associations were stronger among females and younger adults aged 18–39 years. Sleep disorders (SDs) showed the strongest modifying effect in both directions (sub-distribution HR ≈ 1.60). Results were consistent across sensitivity analyses.

This nationwide longitudinal study demonstrates a robust bidirectional association between IBS and psychological distress, supporting integrated screening and multidisciplinary care approaches targeting gut–brain interactions.

People with schizophrenia develop more chronic diseases at a younger age and die younger than people in the general population. It has been hypothesized that this excess morbidity and mortality could be partially due to accelerated aging in schizophrenia. If true, this would motivate the development of ‘gero-protective’ interventions to reduce chronic disease burden in schizophrenia. However, it has been difficult to test this hypothesis, in part, due to the limited ability to measure aging in samples of people with schizophrenia.

We utilized a novel neuroimaging biomarker of the longitudinal pace of aging, DunedinPACNI, to test for accelerated whole-body aging in schizophrenia across four neuroimaging datasets (total N = 2,096, 48% female) accessed through the Lieber Institute for Brain Development, the University of Bari Aldo Moro, and the North American Prodrome Longitudinal Study – 3.

We found consistent evidence of faster DunedinPACNI in schizophrenia compared with controls. In contrast, youth at clinical-high risk for psychosis did not have faster DunedinPACNI compared to controls. Unaffected siblings of patients also did not have faster DunedinPACNI than controls. Faster DunedinPACNI in schizophrenia was not explained by tobacco smoking or antipsychotic medication use.

The results support the hypothesis that schizophrenia is accompanied by accelerated aging. Results were inconsistent with some of the most obvious explanations for accelerated aging in schizophrenia (familial risk, smoking, and iatrogenic medication effects). Research should aim to uncover why people who have schizophrenia age rapidly, as well as the utility of early disease-risk monitoring and anti-aging interventions in schizophrenia.

Neurodevelopmental models regard impulsivity as a central risk factor for adolescent substance use. However, the practical utility of impulsivity in predicting substance use is complicated by variability among measures that encompass multiple methods and theoretical domains. Prior research has been constrained by cross-sectional designs, small sample sizes, and/or the use of a narrow subset of impulsivity measures.

Leveraging the ABCD dataset (n = 11,868), we identified and replicated correlations among impulsivity measures and assessed their prospective longitudinal and concurrent predictive utility regarding adolescent substance use outcomes before 15 years old. We then used simulation to inform how associations between impulsivity and substance use vary across sampling strategies (population vs. high-risk cohorts) and sample sizes.

Correlations between questionnaire and behavioral measures of impulsivity were small, and questionnaires significantly outperformed behavioral measures in predicting substance use initiation, largely due to the contribution of the CBCL externalizing scale. Predictions of substance use based on impulsivity were statistically detectable but small according to clinical standards (AUCs 0.6–0.76), exhibiting sensitivity to sample size and base rate of substance use, and thus, poor absolute predictive performance. Large samples (n > 1,000) were needed to achieve adequate power for impulsivity measures to predict substance use initiation.

These results support a significant but small contribution of impulsivity in predicting the onset of early adolescent substance use, indicating that these factors alone are insufficient for clinically deployable prediction. In community samples, large sample sizes are needed for reproducible impulsivity prediction of adolescent substance use.

Depression is a common comorbidity in neuropsychiatric disorders, affecting a significant proportion of patients with neurodegenerative diseases. Traditional antidepressants show limited efficacy, particularly in cases involving comorbid depressive symptoms, highlighting the need for alternative treatments.

Here we provide the first data on possible benefits of add-on therapy with transcranial pulse stimulation (TPS). Based on the largest patient sample in the emerging field of focused ultrasound (FUS) neuromodulation to date, a retrospective analysis was conducted on 88 patients with various neuropsychiatric diagnoses to evaluate the impact of TPS on depressive symptoms, measured by the Beck Depression Inventory (BDI-II).

The study revealed significant improvements in BDI-II scores posttreatment (N = 88), with the most substantial effects observed in more severely impacted patients: individuals with minimal to severe depression (BDI-II ≥9; N = 32) experienced an average reduction of 5.22 points (29.46%), while those with mild to severe depression (BDI-II ≥14; N = 15) showed an even greater mean improvement of 10.40 points (40.51%). These results surpassed established thresholds for clinical relevance and substantially exceeded placebo effect sizes observed in relevant brain stimulation studies. Moreover, depression score improvement was independent of diagnostic group (dementia, movement disorders, or other), improvement of the primary diagnosis, antidepressant medication, and baseline cognitive status, highlighting the potential of TPS as an effective therapeutic add-on intervention for patients receiving state-of-the-art treatments.

The study’s findings indicate that TPS enhances depression outcomes in neuropsychiatric patients, particularly in those with more severe depressive symptoms.

Persistent affective disturbance is a core, disabling feature of major depressive disorder (MDD), thought to stem from a dysfunctional interaction between emotional bias and cognitive control. However, the underlying neural dynamics are debated, with studies reporting both hyper- and hypoactivation. This study utilized high-temporal-resolution electroencephalogram (EEG) to resolve this discrepancy by examining distinct stages of emotional information processing.

We recruited 175 medication-free patients with MDD (Hamilton Depression Rating Scale-17 ≥ 14) and 101 healthy controls (HCs) who completed an emotional Stroop task while an EEG was recorded. We analyzed event-related potentials reflecting conflict monitoring (N250), inhibition (N450), and resolution (LSP) using a 2 (group) × 2 (valence) × 2 (congruency) analysis of variance.

Results revealed a stage-specific neural cascade. Compared to HCs, the MDD group showed: (1) hypoactivation during initial conflict monitoring (attenuated N250 amplitude); (2) compensatory hyperactivation during conflict inhibition (a significant N450 interaction revealed generalized conflict activity in MDD, unlike the context-specific response in HCs); and (3) subsequent hypoactivation during conflict resolution (reduced LSP amplitude for negative stimuli). Crucially, altered N450 correlated with depression severity, and the entire neural cascade predicted behavioral performance.

The apparent contradiction in the literature reflects a multistage process. MDD is characterized by an inefficient neural cascade: an initial deficit in conflict monitoring is followed by compensatory overactivation during inhibition, which ultimately proves insufficient, leading to impaired late-stage resolution. This temporally specific model advances our understanding of the pathophysiology of depression and identifies potential stage-specific targets for intervention.

Educational attainment (EA), which comprises cognitive (CogEA) and noncognitive (NonCogEA) components, is positively genetically correlated with alcohol and cannabis use but negatively correlated with alcohol and cannabis use disorders (AUD and CUD). These paradoxical associations suggest that shared genetic influences with EA may differ by level of substance involvement.

To test this, we examined the shared genetic architecture of EA, CogEA, and NonCogEA with alcohol consumption (AC), AUD, lifetime cannabis use (CanUse), and CUD. We used bivariate causal mixture models, local genetic correlation analyses, and conditional/conjunctional false discovery rate analyses to identify global, regional, and variant-level overlap for EA and substance-related trait pairs.

EA shared 57.57% of causal variants with AC and 62.42% with AUD, while sharing 48.07% of causal variants with CanUse and 84.18% with CUD. Among shared variants for AC, 48.12% had concordant effects with CogEA and 52.86% with NonCogEA. For AUD, 38.40% and 41.02% of causal variants had concordant effects with CogEA and NonCogEA, respectively. CanUse had higher concordance with CogEA (71.42%) and NonCogEA (65.56%) than CUD (37.97% and 42.23%, respectively). Functional enrichment in brain tissues varied across substance use and EA pairs.

EA is associated with greater alcohol and cannabis use and lower risk for AUD and CUD, a pattern that reflects both concordant and discordant variant effects. CogEA and NonCogEA show partially distinct patterns, particularly for cannabis-related traits, highlighting the importance of disaggregating EA to clarify the genetic architecture underlying its paradoxical associations with substance-related traits.

Extensive evidence links air pollution exposure to cognitive decline; however, it remains unclear whether cognitive reserve and brain reserve modify this association. We examined the moderating roles of cognitive reserve contributors and brain reserve in the association between air pollution and cognitive function in dementia-free adults.

Cross-sectional data were obtained from 650 participants who underwent 3T brain magnetic resonance imaging and completed the Montreal Cognitive Assessment (MoCA). Cognitive reserve contributors were assessed based on education, occupation, and social engagement. Brain reserve was quantified using the ventricle-to-brain ratio derived from brain scans. Five-year average concentrations of particulate matter with diameters ≤10 and ≤2.5 μm and nitrogen dioxide were estimated based on residential addresses. Partial least squares structural equation modeling was applied to construct latent variables representing the air pollution mixture and composite cognitive reserve (contributors). Analyses examined whether cognitive reserve contributors and brain reserve modified associations of air pollution with MoCA scores and suspected mild cognitive impairment.

In individuals with an average level of cognitive reserve, a 1–standard deviation increase in air pollution mixture was associated with a 0.24-point decrease in MoCA scores (95% confidence interval [CI]: −0.31 to −0.16). This association was attenuated in individuals with higher cognitive reserve (β = −0.12; 95% CI: −0.25 to 0.02) and intensified in those with lower cognitive reserve (β = −0.36; 95% CI: −0.37 to −0.35). The moderating effect of brain reserve was not significant.

Higher cognitive reserve may mitigate the effects of air pollution on cognitive function.

Individuals with subthreshold depression (StD), a potentially preclinical stage of major depression, may habitually employ maladaptive expression suppression strategies in emotion regulation. However, the effect of emotional suppression (EES) and underlying neural mechanisms remain unclear.

Data came from two samples (Sample 1: 55 StD, 60 healthy controls (HC); Sample 2: 23 StD, 20 HC). Both samples completed expression suppression tasks. Using drift diffusion modeling, we decomposed performance on the emotional assessment process into separate processing components, particularly the speed of information update (drift rate), to examine how depression and emotional suppression affect decision-making. To further reveal the potential mechanism, we conducted fMRI scanning in Sample 2 and characterized latent neurocircuit driving emotion suppression and drift rate using dynamic causal modeling (DCM).

The EES negatively correlated with drift rate. StD showed reduced efficacy of EES and faster drift rates of negative preference. Greater activation was observed in the dorsolateral prefrontal cortex (dlPFC) and amygdala in StD during suppression. DCM analysis revealed that inefficient EES might be explained by the stronger connection from the right dlPFC to the right amygdala, while the faster drift rate might be attributed to a stronger connection from the left amygdala to the right dlPFC.

Our study uncovered novel latent behavioral and neurocircuit mechanisms of early risk for depression. Ineffective emotional suppression in StD is associated with faster accumulation of negative evidence. The underlying neural mechanism may involve aberrant regulation between the dlPFC and amygdala in negative contexts.

Neurodevelopmental disorders have been associated with hearing problems (HP) later in life, but there is limited information regarding their shared biology.

We leveraged large-scale genome-wide datasets to estimate genetic correlation (global and local), polygenic overlap, and locus-specific pleiotropy among HP, autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and Tourette syndrome (TS). Then, we investigated shared molecular functions, biological processes, and cellular components, and performed a drug-repurposing analysis to identify compounds that may target the pathogenic processes linking neurodevelopmental disorders to HP.

We observed high genetic correlation of HP with ASD (rg = 0.22) and TS (rg = 0.22). With respect to HP-ADHD polygenic overlap, 34% of the causal variants were shared between these conditions, with only 74% of them showing concordant effect directions. We also identified nine chromosomal regions with evidence of ADHD-HP local genetic correlations with pleiotropic effects on other outcomes, such as smoking initiation, brain-imaging phenotypes, and bilirubin levels. With respect to HP-ASD, we observed an inverse local genetic correlation within CD33 chromosomal region. Pleiotropy among HP, ASD, and ADHD was also identified in two variants (rs325485 and rs2207286) included within 95% credible sets related to neuropsychiatric conditions, altered hearing function, and other traits such as risk taking and insomnia. Drug-repurposing analyses identified anisomycin for HP-ASD shared biological mechanisms and five compounds related to HP-ADHD pleiotropy.

Our findings provide evidence that the comorbidity between neurodevelopmental disorders and HP is at least partially due to shared pathogenic processes acting through intrinsic and extrinsic factors.

Menopause is a natural physiological process, but its effects on the brain remain poorly understood. In England, approximately 15% of women use hormone-replacement therapy (HRT) to manage menopausal symptoms. However, the psychological benefits of HRT are not well established. This study aims to investigate the impact of menopause and HRT on mental health, cognitive function, and brain structure.

We analyzed data from nearly 125,000 participants in the UK Biobank to assess associations between menopause, HRT use, and outcomes related to mental health, cognition, and brain morphology. Specifically, we focused on gray matter volumes in the medial temporal lobe (MTL) and anterior cingulate cortex (ACC).

Menopause was associated with increased levels of anxiety, depression, and sleep difficulties. Women using HRT reported greater mental health challenges than post-menopausal women not using HRT. Post-hoc analyses revealed that women prescribed HRT had higher levels of pre-existing mental health symptoms. In terms of brain structure, MTL and ACC volumes were smaller in post-menopausal women compared to pre-menopausal women, with the lowest volumes observed in the HRT group.

Our findings suggest that menopause is linked to adverse mental health outcomes and reductions in gray matter volume in key brain regions. The use of HRT does not appear to mitigate these effects and may be associated with more pronounced mental health challenges, potentially due to underlying baseline differences. These results have important implications for understanding the neurobiological effects of HRT and highlighting the unmet need for addressing mental health problems during menopause.