Genetic and environmental factors contribute to depression. Among the latter, early life adversity and immune dysregulation have been consistently linked with depression. Childhood maltreatment (CM) is believed to induce immune dysregulation later in life. However, it is not known how CM might interact with genetic immune factors to contribute to the occurrence of depression. We investigated how genetic variability in 2370 genes from 20 immune pathways associates with a broadly-defined lifetime depression phenotype at gene- and pathway-level, and how this variability interacts with CM. Depression analysis was carried out in 13,309 individuals (1867 cases) from Generation Scotland (GS). CM interaction analysis was carried out in a subset of 749 individuals (99 cases) from GS and an independent sample of 509 individuals (96 cases) from the German BiDirect (BD) Study for which both genetic and CM data was available. Interactions with different types of CM were tested using the subscales of the childhood trauma questionnaire (CTQ). These results were meta-analyzed to obtain general gene-CM interactions. We found association of the GHR gene (false discovery rate -FDR- = 0.03, z = 4.2) and Reactome "RUNX1-regulated transcription of genes involved in myeloid cell differentiation pathway" (FDR = 0.016, beta = 1.2) with depression in GS. After meta-analysis, 56 immune gene-CM interactions were associated with depression (FDR < 0.05) in both GS and BD. These exert functions in hematopoiesis, pathogen recognition and stress responses, among others. Network analysis suggested macrophages as main expressing cell types. Our results underscore the involvement of hematopoietic alterations and immune gene-CM interactions in the development of depression.

Background:Major depressive disorder (MDD) is heterogeneous in clinical presentation and treatment response. The COORDINATE-MDD consortium identified two magnetic resonance imaging (MRI)-derived neuroanatomical profiles: dimension 1 (D1), with relatively preserved gray and white matter, and dimension 2 (D2), showing widespread reductions aligned with immunometabolic profile. Profiles were associated with distinct responses to selective serotonin reuptake inhibitor (SSRI) antidepressant and placebo (PLA). In this study, we examined electrophysiological correlates of the neuroanatomical profiles and their relationship to treatment outcome. Methods:Baseline resting-state, eyes-closed electroencephalography (EEG) was acquired from 237 medication-free participants with MDD who were in a current depressive episode (155 women; mean age [SD] = 37.47 [13.36] years) from CAN-BIND (Canadian Biomarker Integration Network in Depression) (SSRI) and EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) (SSRI or PLA). EEG features included spectral power, frontal alpha asymmetry (FAA), multiscale sample entropy, and intersite phase clustering. Effects of profile (D1 and D2) and clinical outcome (responder, nonresponder; defined as ≥50% symptom improvement) were examined with age, sex, and site as covariates. Results:No significant electrophysiological differences were observed after covariate adjustment. However, among participants who subsequently responded to treatment, D1 showed greater baseline alpha power in frontal and central regions and lower relative delta posteriorly compared with D2. In PLA-treated responders, D2 showed spectral slowing, elevated low-frequency power, reduced gamma, and coarse-scale entropy compared with D1. Baseline FAA was lower in responders than nonresponders, independent of the neuroanatomical profile. Conclusions:EEG differences between MRI-defined neuroanatomical profiles emerged in relation to clinical outcome. D1 was associated with electrophysiological patterns consistent with flexible, globally regulated cortical dynamics in SSRI responders, whereas D2 showed a distinct pattern in PLA responders, indicating partially separable neural mechanisms underlying pharmacological and PLA treatment effects.

Abstract Background Major depressive disorder (MDD) is clinically heterogeneous, hindering identification of reproducible biomarkers. Using a semi-supervised machine learning approach, HYDRA, we previously identified two neuroanatomical dimensions from structural MRI in medication-free MDD from COORDINATE-MDD consortium. These dimensions (D1, D2) showed differential responses to selective serotonin reuptake inhibitor (SSRI) antidepressants and placebo. External replication in UK Biobank linked D2, characterized by widespread subtle neuroanatomical reductions, to an immuno-metabolic profile. Here, we examined whether these dimensions are detectable early in the course of illness. Methods We applied the pre-trained model to structural MRI data from the multisite PRONIA cohort, comprising individuals with recent-onset depression (ROD; n = 377; mean age 25.8 years, SD 6.0; 51.3% female) and healthy controls (n = 267; mean age 25.5 years, SD 6.4; 61.0% female). Participants were assigned to clusters (C1, C2) corresponding to the previously identified dimensions (D1, D2). Clusters were compared on clinical symptom profiles, peripheral inflammatory markers, and in a subset (n = 107), proteomic ageing indices. Results Two neuroanatomical clusters were identified in PRONIA. C1 (n = 265) showed higher negative symptom severity and elevated interleukin-2 levels. C2 (n = 140) was associated with higher residual proteomic age. Overall depressive symptom severity did not differ significantly between clusters. Conclusions Neuroanatomical dimensions of MDD are reproducible and detectable at illness onset. Associations with negative symptom severity, inflammatory signalling, and proteomic ageing suggest these dimensions capture biologically meaningful heterogeneity early in depression. These findings support a biologically informed framework for stratified treatment approaches in MDD.

Major depressive disorder (MDD) is common and disabling, yet reported brain structural differences vary across studies. Here we performed a large vertex-wise (point-by-point) meta-analysis of cortical thickness and surface area using harmonized magnetic resonance imaging processing across 64 cohorts from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) MDD and Depression Imaging Research Consortium (DIRECT) consortia (5,736 patients; 6,538 controls). We show significantly lower cortical thickness in patients with MDD in multiple brain regions, including the inferior parietal, lateral occipital, superior parietal, medial and lateral orbitofrontal, anterior and posterior cingulate, and precentral gyri, with cortical surface area showing no significant differences. Effects were most pronounced in adults with acute depression, whereas adolescents showed no significant case-control differences. Antidepressant medication use at scanning was associated with more extensive thinning, although effect sizes remained modest (mostly |Cohen's d| < 0.20). This high-resolution, globally generalizable map can support studies of mechanisms and help evaluate structural markers of the clinical course and treatment response.

Background Outcome after stroke varies according to stroke subtype by location, but healthcare systems data studies do not include subtyping information. We linked natural language processing (NLP) of brain imaging reports to routinely collected data to estimate risk of death and other outcomes after stroke subtypes in a nationwide dataset. Methods We applied a previously validated NLP algorithm to all CT and MRI head scan reports in Scotland between 2010 and 2018. We linked the reports to hospital readmissions, prescriptions and death data to identify and characterize people with stroke, and to categorize into deep and cortical ischemic stroke, deep and lobar intracerebral hemorrhage (ICH), subarachnoid hemorrhage, and subdural hemorrhage. We used a matched cohort design, and age- and sex-matched four controls per case who never had a stroke. By subtype, we estimated rehospitalization with stroke, myocardial infarction (MI), cancer, dementia, epilepsy and death, accounting for confounders and competing risk of death. Results From 785,331 people with a head scan, we identified 64,219 with clinical stroke phenotypes (mean age 73.4yrs, 49.5% male), and subtyped 12,616 with deep ischaemic stroke; 14,103 with cortical ischaemic stroke; 1,814 with deep ICH; and 1,456 with lobar ICH. There was higher absolute rate of 1-year hospital readmission for lobar compared with deep ICH (4.9% [95%CI 3.9% - 6.1%] vs 3.4% [2.6% - 4.3%]), higher risk of dementia beyond 6 months after lobar ICH compared to controls than for other stroke subtypes (aHR 3.5 [2.3-5.3]); and higher risk of MI within 6 months of cortical ischemic stroke than for other stroke subtypes (aHR 4.6 [3.4-6.3]). Conclusions NLP of free-text reports linked to coded data successfully subtyped stroke at scale, and we estimated risk of clinically relevant outcomes. Future work should use free text to enable large-scale audit and epidemiology of people with stroke. ### Competing Interest Statement Conflict of Interest Disclosures GM has received consultancy fees from Canon Medical Research, Europe, Ltd. The other authors declare no other conflicts of interest. ### Funding Statement Sources of funding and support: AH is funded by a Medical Research Council (UK)/The Stroke Association fellowship (MR/Z504051/1). This project was funded by the Chief Scientist?s Office (CSO-SCAF/17/01), the Medical Research Council (G0902303/1), the Alzheimer?s Society (486). WNW is supported by CSO and Health Data Research UK. MHI is supported by the Wellcome Trust (220857/Z/20/Z; 226770/Z/22/Z, 104036/Z/14/Z; 216767/Z/19/Z) and by a Research Data Scotland Accelerator Award (RAS-24-2). MM is funded by Health Data Research UK. BA is supported by the Turing Fellowship and Turing project (EP/N510129/1) from The Alan Turing Institute, by Legal and General PLC as part of the Advanced Care Research Centre, and by the National Institute for Health Research (NIHR202639). JMW is part funded by the UK DRI which is funded by UK MRC, Als Soc and ARUK; JMW is also part funded by NIHR. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the NRES Committee Northwest - Greater Manchester East ethics committee (15/NW/0719), and the Public Benefit and Privacy Panel for Health and Social Care (1516-0219) of NHS Scotland. Participant consent was not required. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data is restricted as per Public Health Scotland guidelines, as it relates to individual health records. Data can be made available within the National Safe Haven upon application and approval by Public Health Scotland and the Public Benefit and Privacy panel.

General cognitive function ('g') reflects a broad capacity for flexible information processing, yet how it is supported by brain-wide structural connectivity remains unclear. We mapped this relationship in 38,824 individuals (26-84 years) across three cohorts, showing that g is supported by a widely distributed white matter network whose macroscopic wiring capacity, microstructural organisation, and age sensitivity contribute in distinct ways. Across streamline count (SC), fractional anisotropy (FA), and mean diffusivity (MD) weightings, meta-analytic associations with g were widespread at global, nodal and edge levels, spanning all cerebral lobes and key subcortical structures and dependent on both inter- and intra-hemispheric connectivity, particularly ipsilateral long-range inter-lobar connections. White matter node-g associations spatially mirrored independent cortical morphometry-g associations, indicating convergence of grey and white matter contributions to cognitive performance. Effect sizes increased with age: MD associations became more negative and FA more positive, particularly in frontal regions. Edge-level findings replicated across cohorts and predicted g in a hold-out sample. Together, these findings indicate that g reflects a distributed structural communication backbone whose integrity becomes increasingly relevant across adulthood.

Importance:Preterm birth is a leading cause of atypical brain development and cognitive impairment; however, there are sparse data on its association with statutory educational assessments. Objective:To evaluate school readiness at age 5 years and educational attainment at age 6 to 7 years in children born very preterm and to identify the early-life, neonatal, and socioeconomic factors associated with attainment. Design, Setting, and Participants:This retrospective cohort study included all infants born before gestational age (GA) 32 weeks in England who received care in a neonatal unit and survived to discharge. A linkage between the National Neonatal Research Database and the National Pupil Database was created to integrate neonatal clinical data with educational outcomes. The data analysis was performed between October 1, 2024, and October 31, 2025. Exposure:Gestational age and area-level socioeconomic deprivation. Main Outcomes and Measures:The main outcome was school readiness at age 5 years (as measured by the Early Years Foundation Stage Profile [EYFSP]) and attainment in reading, writing, mathematics, and science at age 6 to 7 years. For each outcome, prevalence of not meeting the expected level of attainment across indices of socioeconomic deprivation and GA stratified by 23 to 26 weeks and 27 to 31 weeks were calculated. Results:Of a total of 15 857 children included (2595 born at GA 23-26 weeks [16.3%] and 13 262 born at GA 27-31 weeks [83.7%]; 8449 boys [53.3%]), 8602 (56.6%) did not meet the school readiness level at age 5 years, and 7789 (51.8%) did not meet expected attainment at age 6 to 7 years for writing, 7216 (48.1%) for math, 6354 (41.9%) for reading, and 5449 (36.0%) for science. Children born at GA 23 to 24 weeks had a higher odds of not meeting expected school readiness levels compared with those born at 31 weeks (adjusted odds ratio [AOR], 2.86 [95% CI, 2.19-3.73]). Children born in areas with the most deprivation had a higher risk of underattainment compared with those in areas with the least deprivation (EYFSP: AOR, 1.27 [95% CI, 1.11-1.45]). In adjusted models, male sex and season of birth were associated with increased risk (EYFSP: AOR, 1.96 [95% CI, 1.82-2.11] and 2.64 [95% CI, 2.41-2.90], respectively) alongside several potentially modifiable risk factors, including smoking during pregnancy (AOR range from 1.19 [95% CI, 1.08-1.31] for math to 1.31 [95% CI, 1.19-1.44] for reading); exposure to postnatal corticosteroids (EYFSP: AOR, 1.37 [95% CI, 1.13-1.65]); severe acquired neonatal brain injuries, particularly periventricular leukomalacia (EYFSP: AOR, 3.05 [95% CI, 2.04-4.58]) and hydrocephalus (EYFSP: AOR, 2.47 [95% CI, 1.48-4.13]); comorbidities of preterm birth, including necrotizing enterocolitis (EYFSP: AOR, 1.60 [95% CI, 1.20-2.14], retinopathy of prematurity (EYFSP: AOR, 1.46 [95% CI, 1.10-1.93], and bronchopulmonary dysplasia (EYFSP: AOR, 1.30 [95% CI, 1.18-1.44]); and nutrition during neonatal care (EYFSP: AOR, 1.19 [95% CI, 1.07-1.33] and 1.51 [95% CI, 1.37-1.66] for mixed feeding and exclusive formula feeding, respectively, vs breastfeeding). Conclusions and Relevance:This cohort study of children born before GA 32 weeks found that preterm birth was associated with a substantial and persistent risk for educational underattainment across early school years, especially when combined with socioeconomic deprivation. Improving outcomes for children born preterm may require reducing social inequalities and minimizing comorbidities of preterm birth. Several modifiable early-life exposures offer practical targets for intervention, including maternal nonsmoking, appropriate corticosteroid use, and breastfeeding. Deferred school entry or targeted academic support may benefit children born very preterm, depending on birth season. These strategies may help parents, clinicians, educators, and policymakers improve long-term educational attainment for children born preterm.

Combining multi-site MRI datasets increases statistical power and model generalisability but may be hindered by variability between sites. Harmonisation methods aim to remove potentially confounding variance while preserving biologically meaningful signals. However, this can be challenging, as each T1-weighted image reflects both scanner properties (e.g., field strength, sequence parameters) and individual biological characteristics (e.g., age, sex, ethno-cultural background, and pathology). Two image-based (HACA3, IGUANe) and two feature-based (neuroHarmonize, neuroCombat) harmonisation methods were assessed using T1-weighted brain imaging data from the Psy-ShareD database; 564 participants (295 schizophrenia, 269 controls) from seven studies acquired across 5 sites from the Psy-ShareD database. We trained several models to classify sites, schizophrenia diagnosis, age, and symptom levels. Site-classification accuracy was high for unharmonised data (90.1%) and for HACA3 (92.2%), slightly reduced with IGUANe (86.6%), and near chance for feature-based methods (4.2% neuroHarmonize; 1.8% neuroCombat), indicating effective bias removal. We fitted several models predicting biological signals including diagnosis, age, and symptom levels across different harmonisation methods. In most cases, classification with harmonised data performed at least as well as with unharmonised data. Generally, feature-based methods best remove site-related variance, but image-based approaches remain a promising avenue for preserving individual biological differences. This work provides practical guidance for selecting harmonisation strategies in multi-site psychiatric neuroimaging, depending on whether the priority is bias reduction or preservation of subject-level variability. ### Competing Interest Statement PA has been funded by FrieslandCampina and Nedra, GKM consults for Ieso Digital Health. RU reports consultancy from Vitaris and Springer Healthcare unrelated to the current work. ### Funding Statement This work was funded by the United Kingdom Medical Research Council grant number MR/X010651/1 and delivered through the National Institute for Health and Care Research (NIHR) Maudsley Biomedical Research Centre (BRC). This work was supported in part by the Japan Agency for Medical Research and Development (AMED) Grant Number JP24wm0625302. All research at the Department of Psychiatry in the University of Cambridge is supported by the NIHR Cambridge Biomedical Research Centre (NIHR203312) and the NIHR Applied Research Collaboration East of England. RU is supported by the NIHR Oxford Health Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. A list of funders and acknowledgements for Psy-ShareD datasets can be found at https://psyshared.com/Team.html ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: London - Dulwich Research Ethics Committee Title of the Research Database: Psychosis MRI Shared Data Resource (Psy- ShareD), V1 REC reference: 25/LO/0184 IRAS project ID: 352347 I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data used in the study is available via the Psychsis MRI ShareD Data Resource (psyshared.com)

Introduction:Successful acquisition of language and literacy skills is essential to child development and is associated with positive socioeconomic and well-being outcomes later in life. Research into communication skills has primarily focused on early development and childhood. This is particularly the case for studies of genetic variation in reading and language skills, which rarely include older adults; the largest genome-wide association study to date includes participants only up to 26 years of age. We argue that reading-related traits remain stable across the adult lifespan and that including older adults offers a way to increase statistical power for gene discovery. Here, we describe newly available reading, spelling and oral-language-related measures in the Generation Scotland: Scottish Family Health Study (GS:SFHS). Methods:Phenotypic data in GS:SFHS were extended to include quantitative measures of reading, spelling and language-related measures as well as self-reported neurodevelopmental and psychiatric conditions. Participants also reported frequency of book reading in both childhood and adulthood. Multiple regression analyses were conducted to examine associations between reading-related measures and age and characterise their stability across the adult lifespan. Results:Reading-related data were collected for N=1595 GS:SFHS participants aged 29.5-76.9 years. Regression analyses indicated that reading and spelling performance were stable across the adult lifespan. In contrast, negative curvilinear effects of age2 were observed with phonological verbal-memory, auditory short-term memory and working memory, indicating decreasing performance with increasing age. Conclusions:These data provide a novel resource for investigating reading, spelling and language skills in adults. The opportunity to link these measures with the existing and future biomarker, cognitive and health record data within GS:SFHS offers a deeply phenotyped dataset with substantial potential for replication studies, meta-analyses and future genetic discovery.

Background:Major depressive disorder (MDD) is associated with altered brain structure and evidence of accelerated brain aging. However, previous studies have been limited by clinical samples with mixed medication status and multiple mood states, modest sample sizes, small percentage of MDD individuals older than 65 years of age, and/or reliance on summary-level data. Methods:Harmonized T1-weighted MRI from MDD (n = 645), all medication-free and in a current depressive episode, and matched healthy controls (n = 645), segmented into 145 regional volumes, from 11 sites in COORDINATE-MDD consortium. Brain age gap (BAG) was estimated using gradient boosting regression with nested cross-validation. Group differences in BAG (and age-corrected BAG [cBAG]) were examined across age strata. Regional contributions were evaluated using Shapley Additive exPlanations. Results:MDD was associated with significantly elevated cBAG compared with healthy controls (mean difference + 2.01 years). Age-stratified analyses showed no differences before mid-30s, with progressively larger gaps thereafter, reaching +6.85 years in MDD aged 55 and older. cBAG differed across neuroanatomical phenotypes associated with differential antidepressant response, cognitive impairment, increased adverse life events, increased self-harm and suicide attempts, and a pro-atherogenic metabolic profile. Key contributing regions included lateral and medial prefrontal regions, middle temporal gyrus, putamen, supplementary motor cortex, central operculum, and cerebellum. Conclusions:Accelerated structural brain aging in MDD is age-dependent and is most pronounced in a neuroanatomical phenotype associated with worse key clinical outcomes. The findings support neuroprogression models of MDD while demonstrating that cBAG is not a uniform feature of MDD and seem to be more strongly expressed in a specifically clinically vulnerable disease phenotype.

Behavioural studies suggest atypical or delayed development of "theory of mind" (ToM; our ability to reason about others' mental states) following preterm birth. Using pre-registered analyses of behavioural and movie-viewing functional magnetic resonance imaging (fMRI) metrics of ToM, we tested for a domain-specific impact of preterm birth (24-32 weeks' gestational age) on theory of mind development at age 5 years. Preterm-born children (n = 52) scored lower than term-born comparators (n = 58) on a linguistic behavioural ToM task, but this difference was primarily driven by differences in receptive language. Neurally, preterm-born children (n = 30) had qualitatively similar responses in brain regions that support ToM reasoning to a short movie to term-born comparators (n = 46), as characterised by four neural metrics; responses to one scene differed as a function of gestational age. Using intersubject correlation analyses, we found that preterm-born children's ToM network responses were more heterogenous than term-born children's responses; however, individual preterm-born children's responses most resembled those observed in same-age term-born children, relative to younger children or other preterm-born children. Taken together, preterm birth does not appear to preclude broadly similar functional development in ToM brain regions by age 5 years.

Abstract Background Chronic pain and depression are prevalent and burdensome conditions that frequently co-occur. Separate neuroimaging studies of each disorder suggest overlapping brain-structure alterations, however, relatively few studies have examined their comorbidity directly, and the neuroanatomical profile of co-occurring chronic pain and depression remains unclear. Methods Using UK Biobank data (n = 71,214), we conducted cross-sectional pairwise association analyses of brain structure (cortical measures, subcortical volumes, and white matter microstructure) comparing participants with current comorbid chronic pain and depression, current chronic pain only, current depression only, and controls. Results Compared with controls, the comorbidity group showed regional differences in cortical surface area and thickness (β range = −0.096 to 0.098, p FDR < 0.05), widespread lower cortical volume (β range = −0.096 to −0.050, p FDR < 0.05), lower thalamic (left: β = −0.048, p FDR = 0.038; right: β = −0.060, p FDR = 0.007), hippocampal (left: β = −0.062, p FDR = 0.035; right: β = −0.088, p FDR = 0.002) and left accumbens volume (β = −0.073, p FDR = 0.011), and evidence of widespread white matter microstructure alterations (fractional anisotropy: β range = −0.116 to −0.080, p FDR < 0.05; mean diffusivity: β range = 0.063 to 0.137, p FDR < 0.05). Pairwise comparisons with the disorder-specific groups also identified several alterations unique to the comorbidity group. Compared to controls, those with chronic pain only had widespread lower cortical surface area and volume (β range = −0.043 to −0.015, pFDR < 0.05), whereas non-comorbid depression showed more regionally specific lower cortical thickness and volume (β range = −0.140 to −0.062, pFDR < 0.05) and lower thalamic volume (left: β = −0.067, p FDR = 0.016; right: β = −0.066, p FDR = 0.015), alongside widespread white matter microstructure deficits (fractional anisotropy: β range = −0.104 to −0.083, p FDR < 0.05; mean diffusivity: β range = 0.079 to 0.149, p FDR < 0.05). Conclusion These results provide a robust characterisation of brain structure alterations in comorbid chronic pain and depression, highlighting a distinct neuroanatomical profile and advancing understanding of underlying neurobiology.

Abstract Background Chronic pain and depression are common disorders and leading causes of disability worldwide. They frequently co-occur and show substantial genetic correlation, indicating a shared genetic basis. However, the locus-specific architecture of this overlap remains poorly characterised and may yield important insights into the pathophysiology of their comorbidity. Methods Using the largest currently available European-ancestry genome-wide association studies of major depressive disorder (MDD) (n = 1,639,572) and multisite chronic pain (MCP) (n = 387,649), we estimated the polygenic overlap between traits using the bivariate causal mixture model (MiXeR), identified shared loci via conjunctional false discovery rate (conjFDR), and tested colocalisation with each trait and genetically regulated gene expression in 13 brain tissues. Results MiXeR analysis demonstrated a high degree of directionally consistent polygenic overlap between MDD and MCP. Subsequent conjFDR analysis identified 375 shared loci, 22 of which showed cross-trait colocalisation between the MDD and MCP signals. Gene mapping and enrichment of shared loci implicated several biological processes, including cadherin-mediated cell-cell adhesion and translational initiation. Gene expression colocalisation in brain tissue highlighted protein phosphatase 6 catalytic subunit ( PPP6C ) and suppressor of cancer cell invasion ( SCAI ) in both disorders. Conclusion Overall, these findings have enhanced our understanding of the complex relationship between chronic pain and depression by identifying potential shared molecular mechanisms that warrant further study as targets for prevention and treatment.

The clinical and biological heterogeneity of major depressive disorder (MDD) may reflect the aggregation of different conditions with distinct pathologies under a single diagnostic label. Neuroanatomical heterogeneity in MDD was examined using a harmonized, age- and sex-matched sample from the ENIGMA MDD consortium (N = 5146; age range: 9-82 years; 64% female). Analyses of global neurostrucutral variability revealed greater cortical thickness heterogeneity in MDD compared with healthy controls (Cohen's d = -0.26). Regionally, increased variability in cortical thickness was most prominent in the cingulate (+6.1 to +6.6% more variation in MDD) and insular (+5.8%) cortices, as well as in the frontal (+5.7 to +6.8%) and temporal (+6.1 to +6.8%) lobes. Heterogeneity in cortical thickness was more pronounced among patients using antidepressant medication (Cohen's d = -0.39). Patient-specific analyses further showed that individuals with markedly increased cortical thickness variability (<5th percentile relative to the normative range) exhibited greater depressive symptom severity than those within the normative range (5th-95th percentile; Cohen's d = 0.19-0.36). Overall, the results indicate that neuroanatomical heterogeneity in MDD is primarily expressed in cortical thickness, offering refined insights into the neurobiological complexity of structural alterations associated with depression. These findings could guide future stratification efforts examining whether regionally confined changes in cortical thickness within areas of pronounced variability reflect clinically meaningful patient subgroups.

Abstract Background Many people with depression do not respond well to the first antidepressant prescribed. Treatment Resistant Depression (TRD) refers to depression which does not respond to multiple subsequent antidepressant treatments. Identifying TRD in routinely-collected health records is challenging due to limited response-related data. Previous studies have used definitions based on the number of antidepressant switches observed. However, these do not account for other features clinically indicative of treatment resistance, such as augmentation of antidepressants with lithium or antipsychotics and switches between antidepressant classes. This study examined definitions of TRD and their impact on the resulting sample across three cohorts. Methods Across the DataLoch, UK Biobank, and Generation Scotland cohorts, we identified cases of depression from primary and secondary care record codes and extracted antidepressant treatment patterns from dispensing/prescribing records (N = 51,283, N = 10,556, and N = 649 respectively). We examined 9 TRD definitions that varied along two axes: the minimum number of switches required (1+, 2 + or 3 + switches), and the inclusion of other clinical features (augmentation and one or more between-class switches) as alternative routes to TRD. We contrasted sample size and characteristics between definitions, and examined factors associated with inclusion versus a reference definition of 2 + switches. Results The reference TRD definition included 10% of depression cases in the routine data collection, but substantially fewer cases (4%) in consented cohorts. More inclusive definitions that required fewer switches or included a between-class switch classified more individuals as TRD, but resulted in a proportionally older, more deprived sample with fewer depression-related health record codes, older age of depression onset, lower symptom severity, and greater use of first-line antidepressants. Requiring more switches (3 + switches) classified fewer individuals as TRD, but resulted in a proportionally younger sample, with more depression-related health record codes, younger age of depression onset, and greater use of antidepressants associated with later in the treatment line (e.g., Tricyclics). Definitions including augmentations resulted in a small increase in sample size without notable change in sample characteristics. Conclusions TRD is underrepresented in consented cohort studies. A definition of TRD that includes 2 + antidepressant switches or augmented antidepressant treatment as indicators balances sample size with depression severity, while incorporating features from real-world treatment journeys. Clinical trial number Not applicable.

Preterm birth is closely associated with immune dysregulation in early life and subsequent learning and psychiatric disorders, but methods for stratifying infants at risk remain elusive. Protein epigenetic Scores (EpiScores) are DNA methylation (DNAm)-based proxies of circulating proteins and can capture health-related exposures such as chronic inflammation. EpiScore of C-reactive protein (DNAm CRP) is associated with inflammatory burden in early life, atypical brain development following preterm birth and adult cognitive ability. To evaluate the utility of neonatal protein EpiScores for predicting childhood cognition, we examined associations of DNAm CRP and 42 other saliva-based EpiScores enriched for inflammatory proteins correlated with low gestational age, with cognition in a cohort of 231 children, including 154 preterm children assessed at 2 years and 127 preterm and term-born children assessed at 5 years. DNAm CRP was negatively associated with 5-year Mullen Scales of Early Learning Composite (ELC) (β = -0.273, p = 0.002). Association magnitudes were larger for children born earlier (DNAm CRP x gestational age, βinteraction = 0.181). DNAm CD209 was positively associated with 5-year ELC (β = 0.267, adjusted p < 0.005). Fourteen other EpiScores were nominally associated with either 2-year Bayley-III Cognitive composite or 5-year ELC (absolute β range 0.180 to 0.245, p < 0.05). For preterm children, associations of DNAm CCL18 with 2-year cognition (β = 0.182, p = 0.039) and of DNAm CRP (β = -0.318, p = 0.021) and DNAm CRTAM (β = -0.307, p = 0.008) with 5-year cognition remained significant after adjustment for inflammatory exposures. We demonstrate associations between a range of neonatal salivary EpiScores and childhood cognition, suggesting the clinical value of EpiScores as early life markers of cognitive ability in children at risk of impairment warrants further investigation.

There is a general conception that mental health problems are increasing in younger generations, though little objective comparisons exist. The current meta-analysis examined changes in subclinical mean-level emotional and behavioral problems among population-based samples of youth (1-18 years) globally over the last four decades. We searched systematically in PubMed, Web of Science, Scopus, EBSCO and Google Scholar with pre-registered criteria [removed for masked review]. Included studies ( k = 175, N = 418,528) used the standardized and cross-culturally validated Child Behavior Checklist with parents, teachers and self-reports. A cross-temporal meta-analysis was conducted with data points between 1981 to 2019. Age, sex, response rate, continent were used as moderators. Meta-regression analyses, with year of data collection as predictor, showed that total emotional and behavioral problems did not change in the past 40 years. However, there was evidence of change in specific problems. We find strong evidence for decreased aggression in children over time (parent report: k = 47, b year = -0.18, p = .009, 95%CI[-0.31,-0.05]; self-report: k = 9, b year = -0.41, p = .006, 95%CI[-0.66,-0.16]). There was evidence of a decrease in parent reported externalizing problems in middle childhood ( k = 60, b year = -0.21, p < .001, 95%CI[-0.30,-0.11]) and specifically in teenage boys ( k = 12, b year = -0.27, p = .049, 95%CI[-0.54,0]). In contrast, there were increases in parent-reported attention ( k = 63, b year= 0.24, p = .004, 95%CI[0.08,0.40]) and thought problems ( k = 40, b year= 0.09, p = .006, 95%CI[0.03,0.15]) for youth overall, and anxiety-depression symptoms specifically in teens ( k = 12, b year = 0.26, p = .011, 95%CI[0.07,0.45]), although with high heterogeneity. In sum, our results do not support concerns that children and young people today experience more emotional and behavioural problems than previous generations, rather, they experience subtly different patterns of difficulties. However, an important limitation of the study is that post COVID-19 changes were not studied.

Bipolar disorder is defined by extreme variability in mood, activity and sleep/wake patterns. To date, studies of sleep and circadian parameters in bipolar disorder have predominantly relied on short term monitoring over 1–2 weeks, leaving a need for approaches that can assess individual-level changes in sleep, activity and mood with high levels of temporal granularity. In the AMBIENT-BD study, we will optimise low intensity ambient and passive data collection techniques. These methods will allow us to infer sleep and circadian timing patterns over extended time periods while developing novel data collection, sharing and analytical methods. In parallel, we will develop data management systems to streamline and optimise data sharing. At its core, our project involves an 18-month prospective study focused on the assessment of sleep/wake patterns and clinical and functional outcomes in individuals with bipolar disorder. Furthermore, in collaboration with Bipolar Scotland, we will deliver a knowledge exchange programme on the theme of ‘Sleep, circadian rhythms and bipolar disorder’. AMBIENT-BD will advance our understanding of symptom trajectories and mechanisms contributing to relapse in bipolar disorder, providing new insights for innovations in clinical management.

Abstract Background Chronic pain and depression are leading causes of disability and frequently co-occur. Depression presents with diverse symptoms, but despite this variability, the prevalence of individual depressive symptoms in chronic pain and the genetic and causal associations linking these traits remain poorly characterised. Methods Using data from 142,688 age- and sex-matched UK Biobank participants, we compared depressive symptom severity levels and item-level Patient Health Questionnaire-9 (PHQ-9) prevalences, spanning affective, cognitive and somatic domains, between participants with and without chronic pain. Using genome-wide association study (GWAS) summary statistics of multisite chronic pain (MCP), major depressive disorder (MDD), and individual symptoms of depression, genetic correlations and bidirectional causal effects between MCP and depressive phenotypes (MDD and individual symptoms) were estimated via linkage disequilibrium score regression (LDSC) and two-sample Mendelian randomisation (MR), respectively. Results Depression (at every severity level) was more common in the chronic pain group compared to controls, with the largest between-group difference for severe symptoms (7.50-fold increase). All individual depressive symptoms were at least 2.79 times as prevalent in chronic pain. Additionally, chronic pain had a significant and positive genetic correlation with MDD (r g = 0.59) and all depressive symptoms (r g = [0.24, 0.55]). MR supported a bidirectional causal association between MCP and MDD (MCP→MDD: OR = 1.85, p FDR < 0.001, MDD→MCP: β = 0.17, p FDR < 0.001). At the symptom level, MR indicated bidirectional effects between MCP and anhedonia (MCP→anhedonia: OR = 1.60, p FDR < 0.001, anhedonia→MCP: β = 0.08, p FDR = 0.005), and unidirectional effects of MCP on appetite/weight gain (OR = 1.90, p FDR = 0.022) and appetite/weight loss (OR = 1.63, p FDR = 0.005), concentration problems (OR = 1.63, p FDR = 0.044), and suicidal thoughts (OR = 1.46, p FDR = 0.021). Additionally, genetic liability to concentration problems was associated with a lower risk of MCP (β = -0.04, p FDR = 0.022). Conclusion Chronic pain is associated with a marked depressive burden spanning all symptom domains. Shared genetic architecture and symptom-specific causal pathways, particularly involving anhedonia, highlight potential targets for improved treatment of comorbid chronic pain and depression.

Background:Recruitment to population-based health studies remains challenging, with difficulties meeting target participant numbers, biosample returns, and achieving a representative sample. Few studies provide evaluations of traditional and web-based recruitment methods particularly for studies with broad inclusion criteria and extended recruitment periods. Generation Scotland (GS) is a family-based cohort study that initiated a new wave of recruitment in 2022 using web-based data collection and remote saliva sampling (for genotyping). Here, we provide an overview of recruitment strategies used by GS over the first 18 months of new recruitment, highlighting which proved most effective and cost-efficient in order to inform future research. Objective:This study evaluated recruitment strategies using four main outcomes: (1) absolute recruitment numbers, (2) sociodemographic representativeness, (3) biosample return rate, and (4) cost per participant. Methods:Between May 2022 and December 2023, recruitment was undertaken via snowball recruitment (through friends and family of existing volunteers), invitations to those who participated in a previous survey (CovidLife: the GS COVID-19 impact survey), and Scotland-wide recruitment through social media (including sponsored Meta-advertisements), news media, and TV advertisement. The method of recruitment was self-reported in the baseline questionnaire. We present absolute recruitment numbers and sociodemographic characteristics by recruitment method and evaluate the saliva sample return rate by recruitment strategy using chi-square tests. The overall cost and cost per participant were calculated for each method. Results:In total, 7889 new participants joined the cohort over this period. Recruitment sources by contribution were social media (n=2436, 30.9%), survey responder invitations (n=2049, 26.0%), TV advertising (n=367, 17.3%), snowball (n=891, 11.3%), news media (n=747, 9.5%), and other methods or unknown (n=399, 5.0%). More females signed up than males (5570/7889, 70.5% female). To date, 83.5% (6543/7836) of participants returned their postal saliva sample, which also varied by demographic factors (3485/3851, 90.5% older than 60 years vs 471/662, 71.1% aged 16-34 years). Average cost per participant across all recruitment strategies was £13.52 (US $16.82). Previous survey recontacting was the most cost-effective (£0.37 [US $0.46]), followed by social media (£14.78 [US $18.39]), while TV advertisement recruitment was the most expensive per recruit (£33.67 [US $41.89]). Conclusions:This study highlights both the challenges and the opportunities in large web-based cohort recruitment. Overall, social media advertising has been the most cost-effective and easily sustained strategy for recruitment over the reported recruitment period. We note that different strategies resulted in successful recruitment over varying timescales (eg, consistent sustained recruitment for social media and large spikes for news media and TV advertising), which may be informative for future studies with different requirements of recruitment periods. Limitations include self-reported methods of recruitment and difficulties in evaluating multilayered recruitment. Overall, these data demonstrate the potential cost requirements and effectiveness of different strategies that could be applied to future research studies.