Neuropsychopharmacology

Major depressive disorder (MDD) is strongly associated with dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, systemic inflammation, and gut microbiota dysbiosis. Although selective serotonin reuptake inhibitors such as escitalopram are standard treatments, their efficacy is often constrained by partial response and gastrointestinal adverse effects. In this 12-week, randomized, double-blind, placebo-controlled trial, we evaluated the clinical efficacy and microecological mechanisms of adjunctive Lactiplantibacillus plantarum PS128 (PS128; 6*1010CFU/day) in MDD patients on stable escitalopram therapy. Adjunctive PS128 significantly enhanced clinical response compared to placebo, yielding substantial reductions in HAMD-17 and MADRS, alongside a higher remission rate. 16S rRNA sequencing and PICRUSt2 profiling revealed that PS128 enriched key short-chain fatty acid producers (Faecalibacterium, Coprococcus), counteracting the Klebsiella expansion seen in placebo. Functionally, PS128 up-regulated neuroprotective cofactor, B vitamins, biosynthesis and down-regulated the neurotoxic kynurenine pathway. Network analysis demonstrated that PS128 maintained a resilient, integrated microbial co-occurrence topology, whereas the placebo network showed structural segregation. This stabilized ecosystem attenuated peripheral inflammatory signaling and normalized salivary cortisol levels. Overall, adjunctive PS128 augments escitalopram efficacy by enhancing gut network stability, supporting cellular energetics, and modulating neuroendocrine activity, offering a promising multimodal strategy for MDD.

Background: As cannabis policy changes in the United States, secondhand cannabis smoke (SCS) is increasingly common, including within families. However, prevalence of exposure and clinical correlates over time in adolescents are not fully understood. Objectives: (1) To estimate the prevalence of SCS and personal cannabis use in US-based teens exposed to SCS, and (2) examine the cognitive trajectories of adolescents exposed to SCS compared to non-exposed peers. Methods: Data from the Adolescent Brain Cognitive Development (ABCD) Study was used. Participants (n=11,316 of full cohort with follow-up data; n=776 with self-reported family SCS exposure) attended yearly visits from ages 11-17, completing substance use interviews, toxicological testing, and the NIH Toolbox Cognitive battery. Youth with SCS but no personal cannabis use (n=419; 47% female) were matched on prenatal substance exposure, family substance use history, and sociodemographics to non-SCS exposed and non-cannabis-using youth with a 1:2 ratio (Controls n=838). Linear mixed-effects models assessed cognitive performance by SCS*age interactions, accounting for random effects of subject and family. Covariates included sex and alcohol, nicotine, and other substance use. Secondary models analyzed performance by cumulative waves of reported SCS exposure interacting with age. Results: Of the full cohort, 6.9% (n=776) reported exposure to SCS. Of these individuals, 46% endorsed lifetime personal cannabis use by age 17, relative to 20% of non-SCS exposed youth (OR=3.83[95%CI:3.29,4.44]). Within matched participants, SCS*age demonstrated a significant interaction on attention and inhibitory control ({beta}=-0.32, p=.028), with SCS demonstrating reduced improvement over time. More waves of exposure were also associated with worse performance over time ({beta}=-0.39, p=.057). Discussion: Almost half of those who had been exposed to SCS endorsed personal cannabis use. Cognitive findings were domain specific, similar to findings in secondhand tobacco: SCS exposed youth showed restricted improvement in attention and inhibitory control by age 17. Public health and policymakers should make efforts to curb youth SCS exposure, given the potential for risk which has not been fully explored to date.

Background: Cognitive impairment is the leading cause of disability in schizophrenia with limited treatments. A major barrier to treatment development is the absence of reproducible, mechanistically grounded neural targets. Cross-sectional studies have identified dorsomedial prefrontal cortex (DMPFC)-somatomotor connectivity as a neural marker of cognitive performance on the Auditory Continuous performance task (ACPT), a measure of attention. To test the stability of this marker, we tested the relationship between DMPFC-somatomotor connectivity and ACPT performance in a longitudinal psychosis sample. Methods: Individuals with early psychosis (n=251) and matched controls (n=90) were enrolled and underwent resting-state neuroimaging and neurocognitive assessment. A subset completed longitudinal assessments over 2-4 years. We calculated DMPFC-somatomotor resting-state functional connectivity using a previously identified DMPFC region and a seed in the somatomotor cortex. We performed linear mixed effects models to predict ACPT performance based on connectivity, time, psychosis type, and their interaction. Results: In the psychosis sample, time (p=.0037) and affective psychosis diagnosis (p<.0001) predicted better ACPT performance. In a model predicting ACPT performance, we observed a significant interaction effect of DMPFC-somatomotor connectivity*psychosis subtype (p=.0079) such that DMPFC-somatomotor connectivity predicted ACPT performance only in individuals with non-affective psychosis (p=.0051). We then tested the specificity of this connectivity-cognitive performance relationship. In a model predicting DMPFC-somatomotor connectivity, only ACPT performance (p=.017), but not fluid cognition, was a significant predictor. Conclusions: DMPFC-somatomotor connectivity is longitudinally associated with cognitive performance in early psychosis. This relationship is strongest in nonaffective psychosis, suggesting a novel, reliable target for intervention for cognitive deficits in early psychosis.

Psychosis has long been conceptualized as a disorder of disrupted hierarchical integration across distributed brain systems, yet it remains unclear whether alterations in macroscale cortical hierarchy are already present before illness onset and are associated with subsequent transition to psychosis. Using connectome gradient mapping, we characterized baseline cortical hierarchical architecture along the unimodal-to-transmodal axis in 580 participants from the NAPLS-3 cohort, including converters (CHR-C, n = 56), non-converters (CHR-NC, n = 434), and healthy controls (HC, n = 90). Group differences were assessed at regional, network, and global levels. Group comparisons revealed that CHR-C individuals, relative to the other two groups, exhibited bidirectional alterations selectively along the sensorimotor-to-association gradient, with reduced values in the visual network alongside elevated values in the default mode network, indicating greater separation between sensory and transmodal systems along the gradient. At the global level, CHR-C showed increased explained variance, range, and variation of this gradient, collectively indicating hierarchical expansion. Notably, greater explained variance of this gradient was associated with a shorter time to conversion to psychosis, while increased gradient range and variation were associated with higher positive symptom severity across CHR individuals. These findings indicate that expansion of the sensorimotor-to-association connectome hierarchy is already present before psychosis onset in individuals who subsequently convert to psychosis. This altered hierarchical organization may reflect greater decoupling between sensory and transmodal systems and may characterize neurobiological changes associated with progression from a clinical high-risk state to psychotic illness.

Adolescent substance use is a major public health concern due to increased risk of future physical and mental health conditions. Fronto-striatal functioning - particularly regarding inhibition and reward processing - may increase vulnerability to high-risk substance use. However, it remains unclear if these neurobiological differences precede substance use or are consequences of it. The ongoing Adolescent Brain Cognitive Development (ABCD) Study follows over 10000 youth, offering an unprecedented opportunity to longitudinally examine substance use patterns throughout development. We utilized family-clustered time-varying Cox proportional hazard models to prospectively examine main and interaction effects of right Inferior Frontal Gyrus (IFG) inhibitory control and bilateral nucleus accumbens (NAc) reward response, alongside early life adversity and peer substance use as predictors of alcohol and cannabis onset in the ABCD Study. We identified a significant crossover interaction such that left NAc activity had a slight positive association with first full alcoholic drink in the context of higher right IFG activity but a negative association in the context of lower right IFG activity. However, peer alcohol and cannabis use emerged as the strongest predictors of outcomes. Alcohol onset was also more common in females, and early life adversity was associated only with cannabis onset. Findings indicate that interactions between inhibition- and reward-related brain regions may impact risk for early substance use onset, but these effects may be modest relative to socioenvironmental factors. Additionally, divergent alcohol and cannabis findings suggest that risk profiles are substance specific. Peer-focused strategies should be considered in preventive efforts.

Background: Substance use is common among individuals with depression. Transcranial magnetic stimulation (TMS) is an effective treatment for depression, but current clinical guidelines have discouraged TMS treatment for individuals with depression and co-occurring substance use given concerns for limited efficacy. However, limited data exists on whether substance use affects response to TMS. Methods: Using electronic health record data from patients who received a standard course of TMS for major depressive disorder at an academic medical center, we investigated associations between substance use frequency and response to TMS, defined as change in Patient Health Questionnaire-9 (PHQ-9) scores. Substance use frequency was extracted for alcohol, cannabis, nicotine, stimulants, benzodiazepines, opioids, inhalants, psychedelics, and other drugs. We performed ANCOVA and multiple regression analyses to predict change in PHQ-9 score based on substance use frequency, controlling for pre-TMS PHQ-9 score, age, sex, and number of TMS sessions received. Results: We extracted data from 219 TMS courses. Alcohol was the substance used most commonly (34.2%), followed by prescription benzodiazepines (28.3%), and prescription stimulants (21.0%). Across all substance categories, substance use was not associated with change in PHQ-9 score (all p > 0.05, Cohens d=0.00 to 0.30). In multiple regression models to compare individual levels of substance use frequency (e.g., daily use vs. no use), level of substance use was not associated with change in PHQ-9 score (all p > 0.05). The range of plausible effects of substance use frequency on PHQ-9 change was generally below the minimal clinically important difference for PHQ-9, suggesting substance use was unlikely to have a meaningful clinical effect on antidepressant response to TMS. Conclusions: Low to moderate substance use does not have a clinically significant effect on antidepressant response to TMS. Low-level substance use should not exclude individuals with depression from receiving TMS.

Suicidal behavior results from complex behavioral and biological changes. Previous cross-sectional studies indicate that proinflammatory immunobiological factors are often increased in close temporal proximity to a suicide attempt. Suicidal individuals may also exhibit a biological trait vulnerability to stress and inflammation, due to persistent epigenetic modifications. We enrolled 130 individuals with major depressive disorder (MDD), 83 with suicidal behavior at intake, and followed them for 12 months with up to eight clinical assessments. Quantification of plasma inflammatory markers and metabolites was performed by high-sensitivity electrochemiluminescence and Ultra High-Performance-Liquid-Mass Spectrometry (UPLC-MS), respectively. Epigenetic changes were identified using Illumina EPIC arrays. We identified 15 genes with altered DNA-methylation associated with suicidal behavior and attempts at baseline. Childhood trauma predicted lifetime suicide attempts and was associated with altered methylation of seven genes. Increased neutrophils and lower plasma serotonin at baseline predicted future suicide attempts over the following year (neutrophil estimate = 0.42, P = 0.016; serotonin OR = 0.58, 95% CI: 0.39-1.13). Utilizing biomarkers from baseline and epigenetic data from the genes with highest predictive values (STBD1 ,PRDM8, and TRIM15), we achieved an area under the curve (AUC) of 0.84 for suicide attempts over the year. Suicidal behavior in MDD was associated with specific epigenetic signatures. Several of the identified genes, such as MAD1L1, have been implicated in psychiatric disease, suicidal behavior and the immune response. These findings support the usefulness of epigenetic and immunometabolic blood markers for identifying suicidal individuals in clinical settings, potentially enhancing preventative efforts.

Background: Major depressive disorder (MDD) is a severe mental illness associated with severe clinical consequences and substantial societal burden. It's characterized by immune-inflammatory dysregulation and immune sensitization. Objective: To determine whether in vitro ketamine attenuates phytohemagglutinin (PHA)/lipopolysaccharide (LPS)-induced immune sensitization in patients with MDD and healthy controls (HCs). Methods: Whole blood from 18 patients with MDD and 18 HCs was stimulated with PHA/LPS and exposed to ketamine (0.3 M, 0.6 M, and 6 M) for 72 hours. Cytokines, chemokines, growth factors, and composite immune profiles, including M1/M2 macrophages, T helper (Th)1/2/17, the immune-inflammatory response system (IRS), and compensatory immunoregulatory system (CIRS), were synthesized and determined. Results: Under PHA and LPS stimulation in vitro, the MDD group exhibited markedly elevated immune profiles, including M1, M2, Th1, Th2, Th17, IRS, CIRS, chemokines, and growth factors, consistent with immune sensitization. Significant group-by-treatment interactions were observed for Th1-Th2, M2, growth factors, IL-12(p70), M1, and chemokines. Ketamine produced minimal changes in HCs but broader suppression in MDD, particularly at the highest concentration, without normalizing the sensitized immune phenotype. Among the immune markers with no notable group-by-treatment interactions, ketamine exerted diagnosis-independent effects, decreasing MIP-1{beta}, IL-1&{beta}, Th1, TNF-{beta} IRS, IFN-{gamma}, and IL-2 compared to the control condition. Conclusions: Ketamine exhibited two distinct immunoregulatory patterns: selective, disease-dependent attenuation of sensitized immune pathways and broader, diagnosis-independent suppression of the stimulated immune response, predominantly at higher concentrations. However, these effects were insufficient to normalize the immune-sensitized phenotype of MDD.

Mood fluctuations in major depressive disorder are difficult to anticipate. The biological neural rhythms that organize mood dynamics over days to weeks remain unknown. In individuals implanted with a chronic neural sensing and stimulation device for treatment-resistant depression, we collected years-long intracranial neural recordings alongside daily mood ratings. Both mood and limbic neural activity fluctuated cyclically with multiday (multidien) periodicities of 2-34 days. An individual's daily phase position within mood cycles tracked depression severity, distinguishing whether symptoms were rising, peaking, or resolving. Neural rhythms led mood cycles and forecast an individual's mood trajectory up to 30 days in advance, outperforming models based on raw neural activity. Electrical stimulation reshaped these rhythms, shifting individuals away from the peak-depression phase of their multidien cycle. Our results identify multidien rhythms as an organizing principle of mood in depression and a forecastable, modifiable target for chronotherapeutic neuromodulation.

Recent large-scale studies have enabled new knowledge about genetic underpinnings of morphological and electrophysiological alterations of the retina. Variation in retinal traits, often of neurodevelopmental origin, have been linked to major psychiatric disorders (MPDs). Here, we investigate the genetic overlap between MPDs and key retinal traits to identify underlying molecular mechanisms. We obtained genome-wide associations studies data for bipolar disorder (BD), major depression (MD), schizophrenia (SCZ), and the retinal traits retinal nerve fibre layer thickness (RNFL), ganglion cell inner plexiform layer thickness (GCIPL), and vertical cup-disc ratio (VCDR). We estimated the number of trait-influencing variants shared between traits with MiXeR and identified shared genetic loci with condFDR. Subsequently, we examined the biological pathways of the genes mapped to shared loci. This revealed that GCIPL shared the most genetic variants with MPDs (~60%), followed by RNFL (~40%), and VCDR (~20%). The genetic variants shared between retinal traits and MPDs showed disorder-specific patterns with more pronounced overlaps of SCZ and BD with RNFL, and MD negatively correlated with GCIPL. Gene-pathway analysis highlighted the importance of GABAergic neurotransmission and a two-stage neurodevelopmental process in SCZ, whereas the role of mitochondria and a weaker developmental component were observed in BD. The results also implicated synaptic functioning and gene-expression processes in MD. Furthermore, polygenic analysis suggested that the genetic architecture of retinal traits can distinguish between MPDs. Our findings indicate shared genetic underpinnings between retinal traits and SCZ, BD, and MD, implicating altered neurodevelopment and neurotransmission underlying the retinal link to major psychiatric disorders.

Major depressive disorder (MDD) has been associated with accelerated structural brain aging, yet whether this reflects a pre-existing neurobiological vulnerability, a dynamic acute state effect, or an accumulating biological residual remains unresolved. Across two longitudinal cohorts (N=3220), including a unique sample of 78 initially healthy individuals who transitioned into their first depressive episode during the study course, we systematically tested all three hypotheses. Patients with diagnosed MDD showed elevated MRI-derived brain age relative to healthy controls (1.4 and 2.5 years across cohorts). For the vulnerability hypothesis, individuals scanned prior to their first episode showed no baseline elevation, despite already demonstrating subclinical elevations in self-reported symptom severity, indicating that advanced brain age does not precede illness onset. For the state hypothesis, we found no acceleration of brain aging following the first depressive episode, and longitudinal brain age trajectories were independent of acute clinical symptom severity. Finally, neither episode duration nor recurrence scaled with brain age. Accelerated brain aging in depression is therefore neither an antecedent vulnerability nor an acute state marker of the first episode, but rather a stable biological feature of a long term illness course.

Background: Metabolomic studies of depression have yielded heterogeneous findings, potentially because metabolic correlates differ across symptoms and metabolic states. We examined symptom-specific metabolomic associations and whether body mass index (BMI) modifies these relationships. Methods: We analyzed 83,717 Estonian Biobank participants (70.6% female) with 249 Nightingale metabolite measures and 14 lifetime depressive symptoms. Logistic regression models progressively adjusted for sociodemographic, lifestyle, medication, and BMI factors. BMI-related attenuation and metabolite x BMI interactions were evaluated, followed by self-organizing map analyses of broader metabolic context. Results: Before BMI adjustment, 660 metabolite-symptom associations were Bonferroni-significant; 136 were significant after BMI adjustment, including 105 retained associations. Weight-related associations showed the strongest BMI dependence: none of 199 weight-gain associations and 2 of 115 weight-loss associations were retained. Among 691 preselected metabolite-symptom pairs, 211 (30.5%) showed significant metabolite x BMI interactions after false discovery rate correction. Six systemic metabolic profiles were identified, but only 3 of 211 BMI-sensitive pairs showed additional profile-dependent heterogeneity. Conclusions: Circulating metabolic correlates of depressive symptoms are heterogeneous and strongly dependent on symptom phenotype and BMI-related metabolic context. These findings suggest that metabolic biomarkers in depression should be interpreted in relation to both symptom presentation and metabolic state rather than as uniform correlates of the disorder.

Communities exposed to flooding can experience markedly different mental health outcomes, yet conventional resilience indicators capture only part of the social and contextual conditions that may explain this variation. This study develops a multilevel and predictive framework for examining community resilience and depressive symptoms following flood exposure in Indonesia. Data were drawn from 20,303 respondents aged 15 years and older nested within 312 communities in the Indonesia Family Life Survey (IFLS-5). Depressive symptoms were assessed using the 10-item Centre for Epidemiologic Studies Depression Scale (CES-D-10), with Rasch Partial Credit Model calibration used to examine measurement properties. Bayesian multilevel models quantified between-community heterogeneity and assessed how far observable structural resources accounted for this variation. Community resilience was represented through two complementary constructs: structural resilience, based on observable socioeconomic and social-capital resources, and Latent Community Protective Capacity (LCPC), a model-derived proxy for residual contextual variation in depressive-symptom risk. Approximately 6 percent of variation was attributable to between-community differences, while observable structural resources explained only part of this heterogeneity. Structural resilience and LCPC were weakly correlated (r = 0.155). Moderation analyses provided no clear evidence that structural resilience altered the flood-depression association, while LCPC showed a directionally consistent but uncertain buffering pattern. Predictive models incorporating community-level information improved discrimination, with the best-performing model reaching an ROC-AUC of approximately 0.71. The findings suggest that observable resource-based indices provide an incomplete account of community-level mental health vulnerability and that residual contextual measures may provide complementary information, while requiring cautious interpretation and independent validation.

A body of research suggests that autistic individuals are less likely to drink alcohol than neurotypicals. However, emerging studies support a link between autism and alcohol use. This complex relationship is also reflected in studies that have examined the genetic overlap between the two traits. However, it is unclear whether there is a direct causal relationship between them. To explore this, we applied a combination of polygenic score and Mendelian randomisation analyses using publicly available genome-wide summary statistics and phenotypic measures of autism and alcohol consumption from UK Biobank. LD score regression analyses did not provide evidence of a genetic correlation between genetic liability for autism and drinks consumed per week (rg=-0.08; CI95%=-0.19, 0.03). Further, findings from polygenic score analyses did not support an association between genetic liability for autism and overall monthly alcohol intake. Univariable Mendelian randomisation analyses showed little evidence for a total effect of autism, attention deficit hyperactivity disorder (ADHD) or depression on overall monthly alcohol consumption. Multivariable Mendelian randomisation analyses also showed little evidence of a direct effect of autism on drinks per week when controlling for ADHD and depression. It is plausible that genetic liability for autism does not directly increase the amount of alcohol consumed but instead operates via commonly co-occurring difficulties in the autistic community. However, our findings may be due to methodological shortcomings, including weak instruments biasing effects towards to the null. Consequently, results should be interpreted with caution and further research conducted to address these issues.

Objective: This study examined the prevalence of psychotic experiences (PE) and how early onset and persistence of PE contribute to risk and severity of mental disorders in adolescents at familial high-risk of schizophrenia (FHR-SZ) or bipolar disorder (FHR-BP) and adolescents from a population-based control group (PBC). Methods: This is the second follow-up of a nationwide cohort study including 522 children at FHR-SZ (N=202), FHR-BP (N=120), and PBC (N=200). Participants were assessed at ages 7, 11, and 15 using a semi-structured interview to evaluate PE and mental disorders. Results: At age 15, adolescents at FHR-SZ reported more PE than PBC over the past six months (current) and the past four years, while adolescents at FHR-BP only reported more current PE. PE reported at two or three timepoints (persistent PE) predicted any Axis I disorder in mid-adolescence, corresponding to three- (OR 2.9, 95% CI [1.5-5.7]) and 21-fold (OR 21.4, 95% CI [2.8-162.3]) increased risks, respectively. Persistent PE also predicted multimorbidity, with three- (OR 2.8, 95% CI [1.0-7.6]) and four-fold (OR 4.1, 95% CI [1.2-14.1]) increased risks, respectively. This was after adjustment for sex, early mental disorders, and familial risk. Conclusions: This study demonstrates a strong link between persistent PE and mid-adolescence mental disorders. Our findings emphasize PE as important risk markers for mental disorders during mid-adolescence and highlight the importance of monitoring children with PE before age 7 who develop persistent symptoms.

Background: Higher Body Mass Index (BMI) is an established risk factor of sleep disturbance. It is not known if the effect is homogeneous across the lifecourse or if there is a particular time point in life that might be best to target. Methods: Two-sample Mendelian randomization (MR) was used to investigated the effect of childhood adiposity (adjusting on adulthood adiposity and obstructive sleep apnea (OSA)) on insomnia, morning chronotype, sleep duration, daytime sleepiness and daytime napping. Similarly, total, and direct effect of adulthood adiposity on these outcomes was explored. We used summary statistics from a genome-wide association study (GWAS) of UK Biobank for childhood and adulthood adiposity (n=453,169) and large-scale consortia of OSA (Million Veteran Program) (n=410,268), insomnia, and chronotype (23andMe) (n=1,978,022 and n=248,1000, respectively). Results: Two-sample univariable MR analysis provided no evidence of an effect of genetically predicted childhood adiposity on later life insomnia (Odds ratio (OR)= 0.94, 95% Confidence interval (CI)= 0.87, 1.03). Whereas, multivariable MR (adjusted for adulthood adiposity) analysis provide strong evidence of direct protective effect of genetically predicted childhood adiposity on later life insomnia (OR= 0.70, CI= 0.64, 0.77). Further, both in univariable and multivariable MR, a strong positive effect of increased childhood body size on morning chronotype was observed (OR= 1.16, CI= 1.01, 1.33 and OR= 1.36, CI= 1.15, 1.62, respectively) after accounting for adulthood body size. In both analysis the estimate did not change considerably after aditionally adjusting for OSA. However, childhood and adulthood adiposity found to be associated with OSA and OSA with insomnia. In both univariable and multivariable analysis, increased body size in adulthood increased the risk of having insomnia and a morning chronotype. Conclusions: The findings suggest that higher body size in childhood is not a risk factor for later life insomnia, whereas higher body size in adulthood was. Further, if healthy body size is maintained in adulthood, high childhood adiposity may decrease the risk of insomnia and increase the risk of being a morning person in later life. Keywords: childhood, adulthood, obesity, insomnia, morning chronotype, medelian randomization

Migraine is a leading cause of disability, yet preventive treatment remains largely empirical despite the availability of several mechanistically distinct therapies. Genetic data can clarify mechanisms and therapeutic hypotheses when association signals are integrated with molecular and clinical data. We meta-analyzed migraine GWAS data from 12 European ancestry cohorts (206,893 cases and 2,093,175 controls) and four African ancestry cohorts (22,115 cases and 178,626 controls). We identified 311 lead variants in European-ancestry analyses and 316 lead variants in trans-ancestry analysis. Fine-mapping and transcriptome-wide analyses prioritized variants and genes implicated in sensory neuronal signaling, vascular tone, and immune regulation, with convergent evidence at several established loci including TRPM8 and PHACTR1. Drug-repurposing analyses identified therapeutic targets and compounds, including established migraine treatments and candidates requiring experimental validation. Genetic correlations, Mendelian randomization, and a phenome-wide scan linked migraine liability to psychiatric, pain, and gastrointestinal phenotypes. Together, these findings expand the known genetic architecture of migraine across ancestries and provide a genetics-led map connecting association signals with biological pathways, multimorbidity and candidate therapeutic mechanisms, providing a foundation for future functional and translational studies.

Obesity is a significant public health concern. Early-onset obesity in the context of rare disease can reflect genetically-mediated pathology or elevated susceptibility through indirect mechanisms. Mapping the diverse characteristics and needs of young people with obesity in the rare disease population is a first step toward mechanistic and translational research. We carried out a retrospective comparative analysis of demographic, genotypic, phenotypic and health service utilisation data for young people with obesity (cases: n=500) and without obesity (controls: n=11,444) from the UK 100,000 Genomes Project rare disease cohort. Cases and controls were recruited prior to genomic diagnosis, across clinical disorder categories. We observed significant association between socioeconomic deprivation and obesity risk. Young people with obesity had significantly higher utilisations of acute care and mental health services, indicating an overall higher health burden. A curated panel of 519 candidate obesity-associated genes demonstrated aggregate association with obesity, although no single gene reached significance. Phenotypic comparison between cases and controls highlighted increased multi-organ and neurological system involvement, highlighting the overlap between neurodevelopmental and obesity risks. Within the case group, we conducted cluster analysis to identify early-onset obesity groups with different phenotypic profiles, potentially arising from different causal pathways - this identified six obesity subgroups of interest, with differing involvement of neurodevelopmental and other systems. Our study confirms that obesity co-occurs with a wide range of factors within the rare disease population, and is associated with significant physical and mental health needs, requiring holistic lifelong care.

Background: Previous trauma research includes many limitations, such as the scarcity of pretraumatic health measurements and assessment of traumatic experiences with a broad scope across the lifespan. To respond to these gaps, we aimed to develop a new, prospective, population-based trauma dataset from childhood to middle age. Methods: We used the Young Finns Study that is a population-based, multi-generational, prospective study (n = 3596 for the main generation). It has started in 1980 (baseline assessment) and includes follow-ups in 1983, 1986, 1989, 1992, 1997, 2001, 2007, 2011/2012, and 2018-2020. From the 38-year follow-up and ten measurement points of the YFS, we collected all relevant trauma variables, including both free-format and structured questions that both the participants and their parents responded to. By a data-driven case-to-case analysis, we developed a scale to numerically capture variation in the quality of the experiences. Results: Our final dataset captured a total of 7769 traumatic experiences. We also developed the Traumatic Experience Severity Scale (TESS), including six subscales such as shamefulness, rarity, danger to life or health, effects on everyday life, human-made physical threat, and whether the target person was within or outside one's household. We also preprocessed the dataset to be later easily interleaved with other psychological, cardiovascular, and epigenetic variables of the YFS. Conclusions: We believe this new trauma dataset with thousands of experiences across the lifespan provides new opportunities to multidisciplinary, lifelong trauma research.

This study investigated bidirectional associations between maternal sleep and depressive symptoms from preconception to postpartum, and whether infant sleep mediated or moderated these associations. We used data from the Generation R Next Study (N=2,294). Maternal sleep (specifically general sleep disturbance, latency, quality, duration, and midpoint) and depressive symptoms were prospectively assessed at five timepoints from preconception to 12-month postpartum. Sleep was self-assessed with the General Sleep Disturbance Scale and Munich Chronotype Questionnaire; depressive symptoms with the Adult Self Report depression/anxiety subscale and Edinburgh Postnatal Depression Scale. Infant sleep (specifically night awakenings, nocturnal sleep duration, and latency) was parent-reported at 1-month postpartum using the Brief Infant Sleep Questionnaire. Bidirectional associations were examined using Autoregressive Latent Trajectory Models with Structured Residuals. The role of infant sleep was examined using mediation and moderation analyses. We found that maternal sleep and depressive symptoms were both stable over time. For sleep quality and disturbance, bidirectional associations suggested slightly stronger effects from depression to sleep (sleep quality:{beta}depression[-&gt;]sleep quality=0.11, 95%CI:0.07 - 0.14; general sleep disturbance:{beta}depression[-&gt;]sleep disturbance=0.14, 95%CI:0.10 - 0.18) than from sleep to depression ({beta}sleep quality/disturbance[-&gt;]depression=0.07 for both, 95%CIs:0.03 - 0.11). For latency, effects were comparable in both directions ({beta}depression[-&gt;]sleep latency=0.06, 95%CI:0.03 - 0.09; {beta}sleep latency[-&gt;]depression=0.05, 95%CI:0.01 - 0.09). The association between depressive symptoms and sleep latency was both mediated (9.7%) and moderated (p<0.05) by infant sleep latency. In conclusion, general maternal sleep disturbance, sleep quality, and sleep latency showed bidirectional associations with depressive symptoms from preconception/early pregnancy onwards. Infant sleep latency may represent a potential modifiable factor within this cycle.