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.

This systematic review and meta-analyses provide the first synthesis of the literature on trait mindfulness and psychotic-like experiences (PLEs). Theoretical models suggest a protective function of mindfulness and it is important to understand any potential role of mindfulness in the prevention and treatment of PLEs. We examined the following: (1) What is the relationship between trait mindfulness and PLEs in nonclinical populations?; and (2) What is the effect of mindfulness-based interventions (MBIs) on PLEs in nonclinical populations? Five databases were searched, and effect sizes were extracted for each study. Seventeen papers were included in the review. Eleven papers explored the relationship between mindfulness and PLEs, and the meta-regression found a small negative association between PLEs and mindfulness (k=8; pooled correlation r=-0.25; 95% confidence interval [CI]: -0.37, -0.13, p<.001). Eight studies investigated the effect of MBIs on PLEs and the summary effect was not significant in the meta-analysis (k=5; pooled standard mean difference=.09; 95% CI: -0.61, 0.79, p=0.80). Overall, the findings suggest that higher levels of mindfulness are associated with reduced PLEs, with no evidence for the effectiveness of MBIs in reducing PLEs. Findings should be interpreted cautiously given the small number of studies and high heterogeneity in the meta-analyses. Future studies are needed to determine whether MBIs might prevent the transition to psychosis or an at-risk mental state and might usefully measure a broader range of clinically relevant outcomes.

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≤2.5μm 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.

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.

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.

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.

Depression is often comorbid with alcohol use problems, and sex differences may further complicate this interplay. We conducted a longitudinal study using a large European adolescent cohort assessed at ages 14 (baseline, BL), 16 (follow-up 1, FU1), 19 (follow-up 2, FU2), and 23 (follow-up 3, FU3). Depression and alcohol use were measured using standardized behavioral scales. Cross-lagged analysis, improved Mendelian randomization (MR) analysis, and mediation analysis were conducted to infer the causal interplay. 2110 adolescents were included at baseline (49% male). Depression and alcohol consumption demonstrated a significant positive correlation (rBL=0.094, pBL=1.58E-05, 95% CI=[0.052, 0.137]), which gradually diminished over time and eventually became significantly negative. Depression and alcohol use problems remained strongly correlated across three timepoints (r>0.074, p<6.76E-03). Cross-lagged analysis suggested that depression predicted future alcohol use problems: βBL-FU1=0.058, p=0.021, 95% CI=[0.009, 0.108]; βFU2-FU3=0.142, p=8.34E-07, 95% CI=[0.113, 0.263]. MR analyses confirmed this causal interplay (rmean=0.043, longitudinal ppermuation<0.001). Interestingly, MR analyses also indicated that alcohol consumption might alleviate depression (rmean=-0.022, longitudinal ppermutation=0.043), particularly in females at FU3, of which the anxiety status and the personality trait neuroticism largely mediated the effect. These findings were validated in an independent matched sample (N=562) from Human Connectome Project. Depression may predict future alcohol use problems, whereas moderate alcohol consumption might alleviate depressive symptoms, especially in females.