Psychological Medicine最新文献

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Background: 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.

Methods: 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: 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.

Conclusions: 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.

Background: 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.

Methods: 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).

Results: 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.

Conclusions: 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.

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

Methods: 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.

Results: 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.

Conclusions: 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.

Background: Depression is often comorbid with alcohol use problems, and sex differences may further complicate this interplay.

Methods: 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.

Results: 2110 adolescents were included at baseline (49% male). Depression and alcohol consumption demonstrated a significant positive correlation (r_BL = 0.094, p_BL = 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: β_BL-FU1 = 0.058, p = 0.021, 95% CI = [0.009, 0.108]; β_FU2-FU3 = 0.142, p = 8.34E-07, 95% CI = [0.113, 0.263]. MR analyses confirmed this causal interplay (r_mean = 0.043, longitudinal p_permuation < 0.001). Interestingly, MR analyses also indicated that alcohol consumption might alleviate depression (r_mean = -0.022, longitudinal p_permutation = 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.

Conclusions: Depression may predict future alcohol use problems, whereas moderate alcohol consumption might alleviate depressive symptoms, especially in females.

Background: 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.

Methods: 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).

Results: 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.

Conclusions: 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.

Background: Large biobanks offer unprecedented data for psychiatric genomic research, but concerns exist about representativeness and generalizability. This study examined depression prevalence and polygenic risk score (PRS) associations in the All of Us data to assess potential impacts of nonrepresentative sampling.

Methods: Depression prevalence and correlates were analyzed in two subsamples: those with self-reported personal medical history (PMH) data (N = 185,232 overall; N = 114,739 with genetic data) and those with electronic health record (EHR) data (N = 287,015 overall; N = 206,175 with genetic data). PRS weights were estimated across ancestry groups. Associations of PRS with depression were examined by state and ancestry.

Results: Depression prevalence varied across states in both PMH (16.7-35.9%) and EHR (0.2-45.8%) data. Concordance between PMH and EHR diagnoses was low (kappa: 0.29, 95% CI: 0.30-0.30). Overall, one standard deviation increase in depression PRS was associated with lifetime depression based on PMH (odds ratio [OR] = 1.05, 95% confidence interval [CI]: 1.04-1.07) and EHR (OR = 1.05, 95% CI: 1.04-1.07). Results were generally consistent by ancestry, with the strongest signal for European ancestry (PMH: OR = 1.10, 95% CI: 1.08-1.12; EHR: OR = 1.07, 95% CI: 1.05-1.10). Associations between PRS and lifetime depression were largely consistent and significant associations varied minimally (ORs = 1.06-1.45) by state of residence in both subsamples.

Conclusions: Recorded depression prevalence by state in All of Us demonstrates a wide range, likely reflecting recruitment differences, EHR data completeness, and true geographic variation; yet PRS associations remained relatively stable. As studies like All of Us expand, accounting for sample composition and measurement approaches will be crucial for generating actionable findings.

Background: Depression in adolescents involves complex interactions among depression, anxiety, sleep disturbances, and suicidal symptoms. Network theory offers insights into dynamic symptom relationships during recovery.

Methods: Of 797 adolescents initially enrolled, 649 with complete baseline data were included in the network analyses; 458 and 277 participants were retained at the 1-month and 3-month follow-ups, respectively. Cross-sectional Gaussian Graphical Models and Cross-Lagged Panel Network (CLPN) analyses examined relationships among nine symptom domains: depression, somatic/subjective anxiety, sleep quantity/quality, daytime insomnia, passive/active sleepiness, and suicidal ideation/tendency. Network centrality and bootstrap validation assessed parameter stability.

Results: Cross-sectional networks showed structural invariance across timepoints (p>0.05). Subjective anxiety demonstrated highest centrality at T0-T1, while somatic symptoms dominated at T2. Depression maintained high closeness centrality throughout. Although betweenness centrality also suggested a central role for depression, its lower stability (CS < 0.5) necessitates a more cautious interpretation of this specific metric. CLPN revealed more predictive relationships during T0→T1 (76.5% significant edges) than T1→T2 (24.7%). Active sleepiness strongly predicted subsequent somatic anxiety (B=0.683) and depression (B=0.647). Suicide ideation-tendency showed stable bidirectional connections. Network stability was excellent (CS>0.5) except betweenness centrality.

Conclusions: Central symptoms evolved during recovery, with subjective anxiety initially dominant but somatic symptoms becoming central over time. The early post-treatment period showed heightened symptom network activity, with sleep disturbances identified as robust predictors of subsequent affective deterioration. Findings support dynamic, network-informed interventions targeting evolving symptom centrality and predictive pathways, particularly addressing sleep-related symptoms and suicide risk during critical recovery phases.

Background: Depressive symptoms are closely associated with cognitive decline and risk of incident dementia, and plasma biomarkers may play a significant role in this relationship. We aimed to investigate the influence of plasma biomarkers and explore the underlying mechanisms.

Methods: This study included 1,658 dementia-free community residents recruited in 2009-2011 from the Shanghai Aging Study. At baseline, we assayed plasma phosphorylated tau 217 (p-tau217) and neurofilament light chain (NfL), and assessed depressive symptoms using the Center for Epidemiologic Studies Depression scale. Cox regression models were performed to estimate the risks of incident dementia and Alzheimer's disease (AD) during the 5-year follow-up. Parallel and serial mediation models were applied to investigate whether plasma p-tau217 and NfL mediated the relationship between depressive symptoms and cognitive decline.

Results: Older adults with depressive symptoms had higher risks of dementia and AD, especially among those with higher concentrations of baseline plasma p-tau217/NfL. Sex-specific analysis revealed that depressive symptoms combined with high plasma NfL increased AD risk in men (hazard ratio, HR [95% confidence interval, CI] = 5.89 [2.01, 17.27], p = 0.001), whereas women with depressive symptoms and high plasma p-tau217 showed higher AD risk (HR [95%CI] = 6.07 [2.82, 13.09], p < 0.001). Parallel mediation analysis revealed that plasma p-tau217/NfL mediated the relationship between depressive symptoms and cognitive decline, respectively. Additionally, serial mediation analysis found p-tau217 precedes NfL within the mediating pathway (β = 0.403, bootstrap 95% CI: 0.347, 0.452).

Conclusions: Plasma p-tau217 and NfL could individually or jointly mediate the relationship between depressive symptoms and cognitive decline.