Migraine is a neurovascular disorder that poses a high burden to Veterans, who face a greater risk than sex-matched individuals in the general population. Genetic research on migraine in Veterans and its link to psychiatric comorbidities is limited. We present a meta-analysis of a genome-wide association study (GWAS) of migraine in a predominantly male sample of over 433,000 Veterans, including 87,859 cases, from the Million Veteran Program (MVP), identifying 49 genome-wide significant loci, with 36 novel to this study, of which 7 replicated in an independent prior GWAS (after Bonferroni correction for number of loci tested). Our analyses revealed 283 genes, including some newly associated with migraine: MAML3, CELF4, IRX1, ASXL1, SPOCD1, CXCL, and TLR4. In silico analyses showed enrichment in brain and uterine tissues, which may reflect broader hormonal or neuroendocrine pathways. Compared to previous migraine GWAS, our results show minimal vascular tissue enrichment, potentially reflecting the sample composition, which was predominantly men and Veterans. Migraine SNP-based heritability was 10% for men and 16% for women, and several sex-specific loci were identified through sex-stratified analyses. Despite high genetic correlations with neuropsychiatric disorders – including post-traumatic stress disorder, depression, and traumatic brain injury – Mendelian randomization analyses found no causal links. Finally, we prioritized potential migraine drug targets, including losmapimod (which reduces production of toxic DUX4 protein) and TLR4 antagonists.

Improving diagnostic accuracy of obsessive-compulsive disorder (OCD) using models of brain imaging data is a key goal of the field, but this objective is challenging due to the limited size and phenotypic depth of clinical datasets. Leveraging the phenotypic diversity in large non-clinical datasets such as the UK Biobank (UKBB), offers a potential solution to this problem. Nevertheless, it remains unclear whether classification models trained on non-clinical populations will generalise to individuals with clinical OCD. This question is also relevant for the conceptualisation of OCD; specifically, whether the symptomology of OCD exists on a continuum from normal to pathological. Here, we examined a recently published "meta-matching" model trained on functional connectivity data from five large normative datasets (N = 45,507) to predict cognitive, health and demographic variables. Specifically, we tested whether this model could classify OCD status in three independent datasets (N = 345). We found that the model could identify out-of-sample OCD individuals. Notably, the most predictive functional connectivity features mapped onto known cortico-striatal abnormalities in OCD and correlated with genetic brain expression maps previously implicated in the disorder. Further, the meta-matching model relied upon estimates of cognitive functions, such as cognitive flexibility and inhibition, to successfully predict OCD. These findings suggest that variability in non-clinical brain and behavioural features can discriminate clinical OCD status. These results support a dimensional and transdiagnostic conceptualisation of the brain and behavioural basis of OCD, with implications for research approaches and treatment targets.

Connections between one of the main outputs of the cerebellar cortex, the lateral cerebellar nuclei (LCN), to reward-related circuits may explain social deficits resulting from cerebellar critical period perturbations. To examine the influence of LCN development on social behavior, local neural activity was manipulated in mice using Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) from postnatal day 21-35. Adolescent social behavior was assessed using a three-chamber assay. Results revealed the LCN perturbation abolished male social preference. LCN manipulated mice were found to have less neural activation (cFos) in the ventral tegmental area, nucleus accumbens, and anterior cingulate cortex (ACC). Additionally, mice that received the excitatory DREADD perturbation showed increased dendritic complexity in the ACC. These results suggest a chronic perturbation in the LCN during juvenile and early adolescent development impacts social behavior and results in changes to cortical activity and structure observed in adolescence.

Intracellular alpha-synuclein aggregates, known as Lewy bodies (LB), are commonly observed in Alzheimer's disease (AD) dementia. Post-mortem studies have shown a higher frequency of neuropsychiatric symptoms among individuals with AD and LB co-pathology. However, the effects of in vivo-measured LB pathology on neuropsychiatric symptoms in AD remain underexplored. This study aimed to evaluate cross-sectional and longitudinal effects of in vivo-measured LB pathology on neuropsychiatric symptoms across the AD continuum. We analyzed data from 1169 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Participants had in vivo measures of LB pathology (assessed using an alpha-synuclein seed amplification assay), amyloid-beta (Aβ) and phosphorylated tau (p-tau) levels in cerebrospinal fluid, and neuropsychiatric symptoms evaluated using the Neuropsychiatric Inventory-Questionnaire (NPI-Q). Logistic and Cox proportional hazards regression models were used to assess cross-sectional and longitudinal effects, respectively, adjusting for age, sex, and cognitive status. Participants had a mean baseline age of 73.05 (SD 7.22) years, 47.13% were women, 426 (36.44%) cognitively unimpaired, and 743 (63.56%) cognitively impaired. In cross-sectional analyses, LB pathology was associated with higher rates of anxiety, apathy, motor disturbances, and appetite disturbances. In longitudinal analyses, LB pathology increased the risk of developing psychosis and anxiety. These effects were independent of Aβ and p-tau. Our results suggest that in vivo-measured LB pathology is closely associated with neuropsychiatric symptoms across the AD continuum. These findings underscore the potential of in vivo LB detection as a marker for identifying individuals at increased risk of neuropsychiatric symptoms, both in clinical trials and in clinical practice.

We investigated whether the brain age gap (BAG)-the difference between chronological age and age estimated from structural MRI scans-is associated with long-term disease course in affective disorders, using a prospective nine-year follow-up design. T1-weighted MRI data were collected at two time points (mean interval = 8.98 ± 2.20 years) from patients with Major Depressive Disorder (MDD; N = 32), Bipolar Disorder (BD; N = 6), and healthy controls (HC; N = 37) across two sites. Using a brain age prediction model trained on a sample of over 10,000 subjects of the German National Cohort (GNC), we estimated individual BAG at baseline and follow-up using gray matter segments derived from MRI images. Employing linear-mixed-effects models, we tested main effects of diagnosis and hospitalizations as well as their interaction with time on BAG. In an exploratory analysis, we tested if BAG at baseline was predictive of hospitalizations during the nine-year follow-up using logistic regression and 10-fold nested cross-validation. MDD patients showed significantly higher BAG compared to HC (2.27 ± 5.68 vs. 1.00 ± 5.12 years, d = -0.23), while BAG in BD patients was descriptively elevated (4.71 ± 5.40 years). In the Münster subsample (N = 52), patients with at least one hospitalization had higher BAG than those without (4.16 ± 5.74 vs. 1.65 ± 5.41 years, d = -0.45). No group-by-time interaction was observed. Higher BAG at baseline predicted hospitalization during follow-up (p = 0.035), although cross-validated prediction accuracy (64.3%) did not reach significance (p = 0.071). BAG remained stable over time and was not influenced by future recurrence, supporting its role as a potential trait-like marker of vulnerability to illness recurrence. While exploratory, these findings suggest that BAG may capture individual risk for future hospitalization in affective disorders.

Pregnancy constitutes a critical window of vulnerability during which maternal and environmental exposures may shape fetal development through epigenetic mechanisms. While prenatal maternal anxiety and exposure to green spaces have been independently associated with child neurodevelopment, their potential interactive effects on neonatal epigenetic profiles remain largely unexplored. This study examined the independent and interactive effects of maternal trait anxiety and residential green space exposure during pregnancy on neonatal DNA methylation (DNAm) of the brain-derived neurotrophic factor (BDNF) gene. A sample of 110 mother-infant dyads was enrolled at delivery. Maternal trait anxiety was assessed using the Stait-Trait Anxiety Inventory (STAI-Y) and infants' BDNF DNAm at birth was assessed in 11 CpG sites in buccal cells. Prenatal residential addresses were geocoded and green space availability within 300, 500, and 1000 m buffers was calculated using the CLCplus Backbone 2021 land cover dataset. Hierarchical linear regression models were adjusted for infant sex and prenatal exposure to PM2.5. Results indicated that higher maternal trait anxiety was associated with increased BDNF DNAm at four CpG sites only among infants with lower exposure to green space within a 300 m buffer. This association was not significant at higher levels of greenness, suggesting a neuroprotective effect of natural environments during gestation. Findings provide novel evidence that urban green space may buffer the biological impact of maternal anxiety on neonatal BDNF methylation. This highlights the importance of integrating psychological and environmental-level exposures to elucidate early-life determinants of neurodevelopment.

Remission and recovery are key treatment goals in psychotic disorders. This was a 12-year follow-up of a single-blind randomized-controlled trial (RCT) comparing 1-year extension of early intervention (EI) (3-year EI) with 1-year step-down standard care (SC) (2-year EI) in patients who had completed 2-year specialized EI service (EASY program) in Hong-Kong. We systematically examined rates and predictors of symptomatic remission (SR), functional recovery (FR), personal recovery (PR), clinical recovery (fulfilled sustained SR and FR) and full recovery (fulfilled clinical recovery and PR) at 12-year follow-up. A comprehensive array of assessments was conducted encompassing premorbid adjustment and schizoid-schizotypal personality-traits (PSST), onset profiles, symptom dimensions, psychosocial functioning and treatment characteristics. LASSO-penalized and multivariate logistic-regression analyses were performed to construct prediction models of various remission/recovery outcomes. Correlational analyses exploring associations of PR with symptom and functional variables were conducted. A total of 106 of 160 of the initial patient cohort completed 12-year follow-up assessment. Rates of SR, FR, PR, clinical recovery and full recovery were 74.5, 24.5, 50.5, 22.6 and 16%, respectively. PSST and baseline functioning represented important predictors of FR and clinical recovery, while Extended EI was retained in prediction models for SR and full recovery. FR constituted a rate-limiting factor for clinical recovery and full recovery attainment. PR was negatively associated with negative and depressive symptoms, and positively related to psychosocial functioning. Our findings of potential effect of extended EI on long-term outcomes, however, should be treated with caution due to attrition bias, and a sizeable proportion of patients were functionally-impaired.

Suicidal ideation (SI) and behavior are complex phenotypes, with multiple contributing risk-factors. This study used longitudinal data from the Million Veteran Program Mental Health Survey to identify SI profiles among Veterans based on trajectories of ideation and depression severity and compared them to a non-suicidal (no-SI) control group. Latent profile analysis (LPA) was performed to identify SI profiles using data from Veterans (n = 34,322) endorsing SI in their electronic health record. LPA identified four highly reproducible SI profiles: mild ideators with and without depression, variable ideators, and persistent ideators. Veterans across the SI profiles were significantly more likely to have diagnoses of suicidal ideation or behavior, mental disorders, and TBI compared to Veterans with no-SI. The variable ideators showed higher rates of comorbid conditions. The mild ideators without depression and persistent ideators had a significantly higher proportion of deaths by suicide than the no-SI Veterans. European and African American GWAS and pan-ancestry meta-analyses of SI profiles compared to no-SI controls were also performed, which identified genome-wide significant loci across all SI profiles proximal to genes implicated in auditory and vestibular functioning, Alzheimer's, diabetes, and asthma. In summary, SI profiles identified were associated with novel genetic variants not identified by previous suicide GWAS studies. Additionally, Veterans within the mild SI profile that did not present with high-risk comorbidities had the highest rate of suicide deaths, indicating the need for upstream suicide risk prevention interventions across the SI risk continuum.