Item-level analyses reveal genetic heterogeneity in neuroticism

Neuroticism is associated with future disease and mortality risks

BACKGROUND

Neuroticism has been associated with numerous health outcomes. However, most research has focused on a single specific disorder and has produced controversial results, particularly regarding mortality risk. Here, we aimed to examine the association of neuroticism with morbidity and mortality and to elucidate how neuroticism affects trajectories from a healthy state, to one or more neuroticism-related disorders, and subsequent mortality risk.

METHODS

We included 483,916 participants from the UK Biobank at baseline (2006-2010). Neuroticism was measured using the Eysenck Personality Questionnaire. Three clusters were constructed, including worry, depressed affect, and sensitivity to environmental stress and adversity (SESA). Cox proportional hazards regression and multistate models were used. Linear regression was used to examine the association between neuroticism and immune parameters and neuroimaging measures.

RESULTS

High neuroticism was associated with 37 non-overlapping diseases, including increased risk of infectious, cardiometabolic, neuropsychiatric, digestive, and respiratory diseases, and decreased risk of cancer. After adjustment for sociodemographic variables, physical measures, healthy behaviors, and baseline diagnoses, moderate-to-high neuroticism was associated with a decreased risk of all-cause mortality. In multistate models, high neuroticism was associated with an increased risk of transitions from a healthy state to a first neuroticism-related disease (hazard ratio [HR] [95% confidence interval (CI)] = 1.09 [1.05-1.13], P  <0.001) and subsequent transitions to multimorbidity (1.08 [1.02-1.14], P  = 0.005), but was associated with a decreased risk of transitions from multimorbidity to death (0.90 [0.84-0.97], P for trend = 0.006). The leading neuroticism cluster showing a detrimental role in the health-illness transition was depressed affect, which correlated with higher amygdala volume and lower insula volume. The protective effect of neuroticism against mortality was mainly contributed by the SESA cluster, which, unlike the other two clusters, did not affect the balance between innate and adaptive immunity.

CONCLUSION

This study provides new insights into the differential role of neuroticism in health outcomes and into new perspectives for establishing mortality prevention programs for patients with multimorbidity.

Comprehensive genome-wide analysis of retinal vessel caliber reveals microvascular-blood pressure pathways: advancing predictive, preventive, and personalized medicine

Background

Retinal vessel caliber is strongly associated with systemic blood pressure (BP); however, the causal relationship between retinal vascular caliber and BP remains unclear. Understanding this relationship is essential for advancing predictive, preventive, and personalized medicine (PPPM) approaches to effectively manage hypertension and its related complications.

Working hypothesis

Microvessel morphology is causally related to blood pressure. By integrating genome-wide association studies, Mendelian randomization analysis, transcriptomic data, and multivariate genomic approaches, this study aims to identify predictive biomarkers, uncover preventive strategies, and develop personalized intervention targets, thereby advancing the principles of 3P medicine for improved cardiovascular health management.

Methods and results

We conducted a comprehensive investigation into the genetic factors underlying retinal vessel calibers and their complex relationship with BP traits. Our genome-wide association study (GWAS) assess retinal vessel calibers-central retinal arteriolar equivalent (CRAE), central retinal venular equivalent (CRVE), and the arteriole-to-venule ratio (AVR)-in a subset of 36,223 individuals of European descent from the UK Biobank. The analysis identified 9, 5, and 4 SNPs located in TNS, Y_RNA, PBLD, C10orf32-ASMT:AS3MT, GNB3:CDCA3, NTN4, COL4 A2, CTD-2378E21.1, WNT7B, VTA1, FCF1, NPLOC4, FUT1 and CSK region, which are significantly associated with CRAE, CRVE, and AVR, respectively. Genetic correlation analysis revealed shared heritability between BP traits and both CRAE and AVR, but not CRVE. Mendelian randomization analysis confirmed bidirectional causal relationships between CRAE and BP traits, whereas CRVE was neither influenced by nor influenced BP traits. To explore the potential regulatory mechanisms, we leveraged transcriptomic data and identified the following causal pathways in vessel tissue: The expression of MRPL23-AS1 and ULK3 was correlated with the elevation of blood pressure SBP and narrowing of the CRAE. Finally, we constructed a multivariable genetic model including CRAE, AVR, SBP, and DBP, suggesting a common driving factor which underlies these traits.

Conclusions

Our study elucidates the complex relationship between BP and retinal vessel caliber, highlighting potential intervention targets for lowering BP and vascular narrowing-related diseases. These findings contribute to the development of tailored prevention and treatment strategies aligned with PPPM principles.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-025-00411-w.

Genome-wide analyses identify 30 loci associated with obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) affects ~1% of children and adults and is partly caused by genetic factors. We conducted a genome-wide association study (GWAS) meta-analysis combining 53,660 OCD cases and 2,044,417 controls and identified 30 independent genome-wide significant loci. Gene-based approaches identified 249 potential effector genes for OCD, with 25 of these classified as the most likely causal candidates, including WDR6, DALRD3 and CTNND1 and multiple genes in the major histocompatibility complex (MHC) region. We estimated that ~11,500 genetic variants explained 90% of OCD genetic heritability. OCD genetic risk was associated with excitatory neurons in the hippocampus and the cortex, along with D1 and D2 type dopamine receptor-containing medium spiny neurons. OCD genetic risk was shared with 65 of 112 additional phenotypes, including all the psychiatric disorders we examined. In particular, OCD shared genetic risk with anxiety, depression, anorexia nervosa and Tourette syndrome and was negatively associated with inflammatory bowel diseases, educational attainment and body mass index.

Shared genetics and causal relationship between sociability and the brain's default mode network

BACKGROUND

The brain's default mode network (DMN) plays a role in social cognition, with altered DMN function being associated with social impairments across various neuropsychiatric disorders. However, the genetic basis linking sociability with DMN function remains underexplored. This study aimed to elucidate the shared genetics and causal relationship between sociability and DMN-related resting-state functional MRI (rs-fMRI) traits.

METHODS

We conducted a comprehensive genomic analysis using large-scale genome-wide association study (GWAS) summary statistics for sociability and 31 activity and 64 connectivity DMN-related rs-fMRI traits (N = 34,691-342,461). We performed global and local genetic correlations analyses and bi-directional Mendelian randomization (MR) to assess shared and causal effects. We prioritized genes influencing both sociability and rs-fMRI traits by combining expression quantitative trait loci MR analyses, the CELLECT framework - integrating single-nucleus RNA sequencing (snRNA-seq) data with GWAS - and network propagation within a protein-protein interaction network.

RESULTS

Significant local genetic correlations were identified between sociability and two rs-fMRI traits, one representing spontaneous activity within the temporal cortex, the other representing connectivity between the cingulate and angular/temporal cortices. MR analyses suggested potential causal effects of sociability on 12 rs-fMRI traits. Seventeen genes were highly prioritized, with LINGO1, ELAVL2, and CTNND1 emerging as top candidates. Among these, DRD2 was also identified, serving as a robust internal validation of our approach.

CONCLUSIONS

By combining genomic and transcriptomic data, our gene prioritization strategy may serve as a blueprint for future studies. Our findings can guide further research into the biological mechanisms underlying sociability and its role in the development, prognosis, and treatment of neuropsychiatric disorders.

Using human genetics to understand the epidemiological association between neuroticism and lung cancer

Background

Neuroticism, a personality trait characterized by emotional instability, has been linked to an increased risk of lung cancer (LC). However, the genetic underpinnings of this association remain poorly understood. This study aimed to comprehensively dissect the genetic link underlying neuroticism and LC.

Methods

We used genome-wide association study (GWAS) data to investigate the intricate genetic relationship between neuroticism and LC, along with specific histological subtypes: lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), and small-cell LC (SCLC). Our analytical framework encompassed global and local genetic correlation, cross-trait meta-analysis, transcriptome-wide association study (TWAS), and bidirectional Mendelian randomization (MR) analysis.

Results

Notable genetic correlations were found between neuroticism and overall LC (rg=0.15, P=2.24×10-5), with stronger associations observed for LUSC (rg=0.21, P=3.39×10-6) and SCLC (rg=0.16, P=2.50×10-3). Partitioning the genome revealed additional genetic correlations in specific local genomic regions (including chr6q27 and chr6q16.2-q16.3) and functional categories (such as H3K27ac and H3K9ac). The cross-trait meta-analysis revealed 24 genetic loci that influenced both traits, including four novel ones. Looking into the gene-tissue level, TWAS identified 35 genes associated with both neuroticism and LC across multiple tissues, particularly in the nervous, respiratory, cardiovascular, and endocrine systems. MR analysis indicated a potential causal effect of neuroticism on overall LC [odds ratio (OR) =1.48, P=5.53×10-4] and LUSC (OR =1.52, P=8.00×10-3), but not on LUAD or SCLC. No reverse causality was observed.

Conclusions

This study reveals a genetic link between neuroticism and LC, offering new insights into LC risk assessment and potential prevention strategies for individuals with high neuroticism levels.

Exome sequencing identifies protein-coding variants associated with loneliness and social isolation

BACKGROUND

Loneliness and social isolation are serious yet underappreciated public health problems, with their genetic underpinnings remaining largely unknown. We aimed to explore the role of protein-coding variants in the manifestation of loneliness and social isolation.

METHODS

We conducted the first exome-wide association analysis on loneliness and social isolation, utilizing 336,115 participants of white-British ancestry for loneliness and 346,115 for social isolation. Sensitivity analyses were performed to validate the genetic findings. We estimated the genetic burden heritability of loneliness and social isolation and provided biological insights into them.

RESULTS

We identified six novel risk genes (ANKRD12, RIPOR2, PTEN, ARL8B, NF1, and PIMREG) associated with loneliness and two (EDARADD and GIGYF1) with social isolation through analysis of rare coding variants. Brain-wide association analysis uncovered 47 associations between identified genes and brain structure phenotypes, many of which are critical for social processing and interaction. Phenome-wide association analysis established significant links between these genes and phenotypes across five categories, mostly blood biomarkers and cognitive measures.

LIMITATIONS

The measurements of loneliness and social isolation in UK Biobank are brief for these multi-layer social factors, some relevant aspects may be missed.

CONCLUSIONS

Our study revealed 13 risk genes associated with loneliness and 6 with social isolation, with the majority being novel discoveries. These findings advance our understanding of the genetic basis of these two traits. The study provides a foundation for future studies aimed at exploring the functional mechanisms of these genes and their potential implications for public health interventions targeting loneliness and social isolation.

Artificially Sweetened Food Mediates the Perception of Chronic Pain in Individuals With Neuroticism Traits: A Mendelian Randomization Study

BACKGROUND

Previous studies have shown that neuroticism and artificially sweetened food all play essential roles in chronic pain to varying degrees. However, it is unclear precisely the causal relationship between neuroticism traits and chronic pain and whether an unhealthy sweetened food is a mediator in this process.

METHODS

This study employed rigorous research methods to ensure the validity of the findings. We utilized Mendelian randomization (MR) to examine the causal relationships between neuroticism traits, artificially sweetened food, and chronic pain. The data encompass four neuroticism traits (neuroticism, experiencing mood swings, depressed affect, and worry), consumption levels of nine artificially sweetened foods, and seven types of chronic pain. The primary statistical method employed was inverse variance weighting (IVW). Eventually, we explored whether artificially sweetened food serves as a mediator in the relationship between neuroticism traits and chronic pain.

RESULTS

We found that genetic predisposition to higher neuroticism traits and the consumption of artificial sweeteners is associated with an increased risk of chronic pain across multiple sites. Reverse MR analysis also confirms that chronic pain at multiple sites similarly increases the risk of neuroticism traits. Two-step MR suggests the mediating effects of five artificial sweeteners on sciatica: low back pain, thoracic pain, low back pain, joint pain, and muscular pain. These findings could inform interventions and treatments for chronic pain.

CONCLUSION

Neuroticism traits and chronic pain have causal relationships, with artificially sweetened food mediating the pathway from neuroticism traits to chronic pain.

Neuroticism and asthma: Mendelian randomization analysis reveals causal link with mood swings and BMI mediation

BACKGROUND

Neuroticism has been associated with asthma, but the nature of this relationship remains unclear due to limited understanding of the impact of psychological factors on asthma risk. While Neuroticism is known to affect various health outcomes, its specific role in respiratory conditions like asthma is not fully understood.

METHODS

We conducted Mendelian randomization (MR) analyses using genome-wide association studies (GWAS) to explore the causal link between 12 Neuroticism traits and asthma. Various MR approaches, including MR-PRESSO, were employed, with validation through independent GWAS and the FinnGen dataset.

RESULTS

MR-PRESSO revealed a significant causal relationship between mood swings and asthma (OR: 1.927, 95% CI: 1.641-2.263), surpassing the Bonferroni-corrected threshold (p < 4.167 × 10-³). Mood swings emerged as the only significant trait associated with asthma, with reverse MR analyses showing no causal links for other traits. Secondary analyses supported these findings. Multivariate analysis showed mood swings increased asthma risk, independent of smoking, BMI, and air pollution. Mediation analysis indicated that BMI partially mediates the mood swing-asthma relationship, accounting for 9.87% of the effect (95% CI: 4.54%-15.2%, p = 2.850 × 10-4).

CONCLUSION

Mood swings elevate asthma risk, with BMI partially mediating this effect, highlighting a potentially significant pathway through which psychological traits influence asthma.

Polygenic overlap of substance use behaviors and disorders with externalizing and internalizing problems independent of genetic correlations

BACKGROUND

Externalizing and internalizing pathways may lead to the development of substance use behaviors (SUBs) and substance use disorders (SUDs), which are all heritable phenotypes. Genetic correlation studies have indicated differences in the genetic susceptibility between SUBs and SUDs. We investigated whether these substance use phenotypes are differently related to externalizing and internalizing problems at a genetic level.

METHODS

We analyzed data from genome-wide association studies (GWAS) of four SUBs and SUDs, five externalizing traits, and five internalizing traits using the bivariate causal mixture model (MiXeR) to estimate genetic overlap beyond genetic correlation.

RESULTS

Two distinct patterns were found. SUBs demonstrated high genetic overlap but low genetic correlation of shared variants with internalizing traits, suggesting a pattern of mixed effect directions of shared genetic variants. Conversely, SUDs and externalizing traits exhibited considerable genetic overlap with moderate to high positive genetic correlation of shared variants, suggesting concordant effect direction of shared risk variants.

CONCLUSIONS

These results highlight the importance of the externalizing pathway in SUDs as well as the limited role of the internalizing pathway in SUBs. As MiXeR is not intended for the identification of specific genes, further studies are needed to reveal the underlying shared mechanisms of these traits.

The causal role of male pubertal timing for the development of externalizing and internalizing traits: results from Mendelian randomization studies

BACKGROUND

Preexisting epidemiological studies suggest that early pubertal development in males is associated with externalizing (e.g. conduct problems, risky behavior, and aggression) and internalizing (e.g. depression and anxiety) traits and disorders. However, due to problems inherent to observational studies, especially of residual confounding, it remains unclear whether these associations are causal. Mendelian randomization (MR) studies take advantage of the random allocation of genes at conception and can establish causal relationships.

METHODS

In this study, N = 76 independent genetic variants for male puberty timing (MPT) were derived from a large genome-wide association study (GWAS) on 205,354 participants and used as an instrumental variable in MR studies on 17 externalizing and internalizing traits and psychopathologies utilizing outcome GWAS with 16,400-1,045,957 participants.

RESULTS

In these MR studies, earlier MPT was significantly associated with higher scores for the overarching phenotype of 'Externalizing Traits' (b = -0.03, 95% CI [-0.06, -0.01]). However, this effect was likely driven by an earlier age at first sexual contact (b = -0.17, 95% CI [-0.21, -0.13]), without evidence for an effect on further externalizing phenotypes. Regarding internalizing phenotypes, earlier MPT was associated with higher levels of the 'Depressed Affect' subdomain of neuroticism (b = -0.04, 95% CI [-0.07, -0.01]). Late MPT was related to higher scores of internalizing traits in early life (b = 0.04, 95% CI [0.01, 0.08]).

CONCLUSIONS

This comprehensive MR study supports a causal effect of MPT on specific traits and behaviors. However, no evidence for an effect of MPT on long-term clinical outcomes (depression, anxiety disorders, alcohol dependency, cannabis abuse) was found.

Encoding of pretrained large language models mirrors the genetic architectures of human psychological traits

Recent advances in large language models (LLMs) have prompted a frenzy in utilizing them as universal translators for biomedical terms. However, the black box nature of LLMs has forced researchers to rely on artificially designed benchmarks without understanding what exactly LLMs encode. We demonstrate that pretrained LLMs can already explain up to 51% of the genetic correlation between items from a psychometrically-validated neuroticism questionnaire, without any fine-tuning. For psychiatric diagnoses, we found disorder names aligned better with genetic relationships than diagnostic descriptions. Our results indicate the pretrained LLMs have encodings mirroring genetic architectures. These findings highlight LLMs' potential for validating phenotypes, refining taxonomies, and integrating textual and genetic data in mental health research.

Intergenerational transmission of polygenic predisposition for neuropsychiatric traits on emotional and behavioural difficulties in childhood

Childhood emotional and behavioural difficulties tend to co-occur and often precede diagnosed neuropsychiatric conditions. Identifying shared and specific risk factors for early-life mental health difficulties is therefore essential for prevention strategies. Here, we examine how parental risk factors shape their offspring's emotional and behavioural symptoms (e.g. feelings of anxiety, and restlessness) using data from 14,959 genotyped family trios from the Norwegian Mother, Father and Child Cohort Study (MoBa). We model maternal reports of emotional and behavioural symptoms, organizing them into general and specific domains. We then investigate the direct (genetically transmitted) and indirect (environmentally mediated) contributions of parental polygenic risk for neuropsychiatric-related traits and whether these are shared across symptoms. We observe evidence consistent with an environmental route to general symptomatology beyond genetic transmission, while also demonstrating domain-specific direct and indirect genetic contributions. These findings improve our understanding of early risk pathways that can be targeted in preventive interventions aiming to interrupt the intergenerational cycle of risk transmission.

Unraveling the brain-joint axis: genetic, transcriptomic, and cohort insights from neuroticism to osteoarthritis

The causal relationships between neuroticism and osteoarthritis (OA) were inconclusive in observational studies. We conducted bidirectional two-sample Mendelian randomization (MR) and transcriptome-wide association studies to determine the associations and the underlying transcriptomic basis. The summary-level genome-wide association study data for any site OA, knee OA, erosive hand OA, and hip OA were mainly derived from UK Biobank, and neuroticism was derived from CTGlab. We then utilized weighted regression and propensity score matching (PSM) models to investigate the relationship between neuroticism and OA in 11,948 participants of European ancestry from the National Health and Nutrition Examination Survey from 2005 to 2018. Bidirectional two-sample MR studies revealed that feelings of being fed-up, a sense of miserableness, mood swings, and a higher neuroticism score were all linked to an increased risk of OA. These factors were specifically associated with OA at various sites, including the knee. Conversely, there was no evidence to suggest that OA had any influence on traits related to neuroticism. In a comprehensive analysis that accounted for variables such as age, sex, blood lipids, blood glucose, body weight, smoking, alcohol consumption, and physical activity, it was determined that mental fluctuation significantly increased the incidence of self-reported OA (OR 1.37, 95% CI 1.20-1.58, P < 0.001) based on weighted regression. Further confirmation was provided by PSM analysis, which showed that mental fluctuation was associated with a higher incidence of self-reported OA (OR 1.28, 95% CI 1.08-1.52, P = 0.004). Moreover, differentially expressed genes were enriched in several biological processes, including the cell cycle, lipid metabolism, RNA processing, and immuno-inflammatory responses. The results revealed significant genetic and population-based associations, as well as underlying mechanisms, between neuroticism and osteoarthritis, supporting the concept of a brain-joint axis.

Embracing complexity in psychiatry-from reductionistic to systems approaches

The understanding and treatment of psychiatric disorders present unique challenges due to these conditions' multifaceted nature, comprising dynamic interactions between biological, psychological, social, and environmental factors. Traditional reductionistic approaches often simplify these conditions into linear cause-and-effect relationships, overlooking the complexity and interconnectedness inherent in psychiatric disorders. Advances in complex systems approaches provide a comprehensive framework to capture and quantify the non-linear and emergent properties of psychiatric disorders. This Personal View emphasises the importance of identifying rules for generative models that govern brain and behaviour over time, which might contribute to personalised assessments and interventions for psychiatric disorders. For instance, mood fluctuations in bipolar disorder can be understood through dynamical systems modelling, which identifies modifiable parameters, such as circadian disruption, that can be addressed through targeted therapies such as light therapy. Similarly, recognition of depression as an emergent property arising from complex interactions highlights the need for integrated treatment strategies that enhance adaptive reactions in the individual. A framework for quantifying multilevel interactions and network dynamics can help researchers and clinicians to understand the interplay between neural circuits, behaviours, and social contexts. Probabilistic models and self-organisation concepts contribute to building concrete dynamical systems models of mental disorders, facilitating early identification of risk states and promoting resilience through adaptive interventions delivered with optimal timing. Embracing these complex systems approaches in psychiatry could capture the true nature of psychiatric disorders as properties of a dynamic complex system and not the manifestation of any lesion or insult. This line of thinking might improve diagnosis and treatment, offering new hope for individuals affected by psychiatric conditions and paving the way for more effective, personalised mental health care.

Genetic Correlates of Treatment-Resistant Depression

Importance

Treatment-resistant depression (TRD) is a major challenge in mental health, affecting a significant number of patients and leading to considerable burdens. The etiological factors contributing to TRD are complex and not fully understood.

Objective

To investigate the genetic factors associated with TRD using polygenic scores (PGS) across various traits and explore their potential role in the etiology of TRD using large-scale genomic data from the All of Us (AoU) Research Program.

Design, Setting, and Participants

This study was a cohort design with observational data from participants in the AoU Research Program who have both electronic health records and genomic data. Data analysis was performed from March 27 to October 24, 2024.

Exposures

PGS for 61 unique traits from 7 domains.

Main Outcomes and Measures

Logistic regressions to test if PGS was associated with treatment-resistant depression (TRD) compared with treatment-responsive major depressive disorder (trMDD). Cox proportional hazard model was used to determine if the progressions from MDD to TRD were associated with PGS.

Results

A total of 292 663 participants (median [IQR] age, 57 (41-69) years; 175 981 female [60.1%]) from the AoU Research Program were included in this analysis. In the discovery set (124 945 participants), 11 of the selected PGS were found to have stronger associations with TRD than with trMDD, encompassing PGS from domains in education, cognition, personality, sleep, and temperament. Genetic predisposition for insomnia (odds ratio [OR], 1.11; 95% CI, 1.07-1.15) and specific neuroticism (OR, 1.11; 95% CI, 1.07-1.16) traits were associated with increased TRD risk, whereas higher education (OR, 0.88; 95% CI, 0.85-0.91) and intelligence (OR, 0.91; 95% CI, 0.88-0.94) scores were protective. The associations held across different TRD definitions (meta-analytic R2 >83%) and were consistent across 2 other independent sets within AoU (the whole-genome sequencing Diversity dataset, 104 388, and Microarray dataset, 63 330). Among 28 964 individuals followed up over time, 3854 developed TRD within a mean of 944 days (95% CI, 883-992 days). All 11 previously identified and replicated PGS were found to be modulating the conversion rate from MDD to TRD.

Conclusions and Relevance

Results of this cohort study suggest that genetic predisposition related to neuroticism, cognitive function, and sleep patterns had a significant association with the development of TRD. These findings underscore the importance of considering psychosocial factors in managing and treating TRD. Future research should focus on integrating genetic data with clinical outcomes to enhance understanding of pathways leading to treatment resistance.

Genomic Taxometric Analysis of Negative Emotionality and Major Depressive Disorder Highlights a Gradient of Genetic Differentiation across the Severity Spectrum

A core question in both human genetics and medicine is whether clinical disorders represent extreme manifestations of continuous traits or categorically distinct entities with unique genetic etiologies. To address this question, we introduce Genomic Taxometric Analysis of Continuous and Case-Control data (GTACCC), a novel method for systematically evaluating continuity and differentiation of traits across the severity spectrum. GTACCC's key innovation lies in binarizing continuous data at multiple severity thresholds, enabling the estimation of genetic continuity and differentiation within the trait and in its relation to other traits via multivariate models. We apply GTACCC to self-reported neuroticism data from UK Biobank (N= 414,448) and clinically ascertained major depressive disorder (MDD) data from the Psychiatric Genomics Consortium ( Σ N e f f = 111,221 ). We find that while neuroticism shares a considerable portion of its genetic etiology with MDD across the nonclinical, and even very low, range of (r g ∼ . 50 ), genetic sharing increases monotonically across the severity spectrum, approaching unity only at the highest levels of severity (r g ∼ 1.0 ). Genomic structural equation models indicate that a single liability threshold model of negative emotionality is less consistent with the data than a multifactor model, suggesting that a gradient of genetic differentiation emerges across the spectrum of negative emotionality. Thus, within continuous measures of negative emotionality, partly distinct genetic liabilities exist at varying severity levels, with only the most severe levels associated with liabilities that approach equivalence to MDD genetics.

Large-scale exome sequencing identified 18 novel genes for neuroticism in 394,005 UK-based individuals

Existing genetic studies of neuroticism have been largely limited to common variants. Here we performed a large-scale exome analysis of white British individuals from UK Biobank, revealing the role of coding variants in neuroticism. For rare variants, collapsing analysis uncovered 14 neuroticism-associated genes. Among these, 12 (PTPRE, BCL10, TRIM32, ANKRD12, ADGRB2, MON2, HIF1A, ITGB2, STK39, CAPNS2, OGFOD1 and KDM4B) were novel, and the remaining (MADD and TRPC4AP) showed convergent evidence with common variants. Heritability of rare coding variants was estimated to be up to 7.3% for neuroticism. For common variants, we identified 78 significant associations, implicating 6 unreported genes. We subsequently replicated these variants using meta-analysis across other four ancestries from UK Biobank and summary data from 23andMe sample. Furthermore, these variants had widespread impacts on neuropsychiatric disorders, cognitive abilities and brain structure. Our findings deepen the understanding of neuroticism's genetic architecture and provide potential targets for future mechanistic research.

Genomics-driven integrative analysis highlights immune-related plasma proteins for psychiatric disorders

BACKGROUND

Genome-wide association studies (GWAS) have identified numerous variants associated with psychiatric disorders. However, it remains largely unknown on how GWAS risk variants contribute to psychiatric disorders.

METHODS

Through integrating two largest, publicly available, independent protein quantitative trait loci datasets of plasma protein and nine large-scale GWAS summary statistics of psychiatric disorders, we first performed proteome-wide association study (PWAS) to identify psychiatric disorders-associated plasma proteins, followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, we conducted Mendelian randomization (MR) and Bayesian colocalization (COLOC) analyses, with both discovery and parallel replication datasets, to further identify protein-disorder pairs with putatively causal relationships. We finally prioritized the potential drug targets using Drug Gene Interaction Database.

RESULTS

PWAS totally identified 112 proteins, which were significantly enriched in biological processes relevant to immune regulation and response to stimulus including regulation of immune system process (adjusted P = 1.69 × 10-7) and response to external stimulus (adjusted P = 4.13 × 10-7), and viral infection related pathways, including COVID-19 (adjusted P = 2.94 × 10-2). MR and COLOC analysis further identified 26 potentially causal protein-disorder pairs in both discovery and replication analysis. Notably, eight protein-coding genes were immune-related, such as IRF3, CSK, and ACE, five among 16 druggable genes were reported to interact with drugs, including ACE, CSK, PSMB4, XPNPEP1, and MICB.

CONCLUSIONS

Our findings highlighted the immunological hypothesis and identified potentially causal plasma proteins for psychiatric disorders, providing biological insights into the pathogenesis and benefit the development of preventive or therapeutic drugs for psychiatric disorders.

Exploring the bidirectional causality between neuroticism and frailty: a Mendelian randomization analysis

BACKGROUND

Epidemiological studies have confirmed the relationship between personality trait neuroticism and physical health. However, the relationship between neuroticism and frailty remains unconfirmed. This study employed a bi-directional two-sample Mendelian randomization (MR) approach to investigate the causal relationship between neuroticism and frailty.

METHODS

The neuroticism genome-wide association study (GWAS) data from the UK Biobank contained twelve neuroticism-related traits with 489,212 participants. The genetic frailty index data were extracted from the UK Biobank and Swedish TwinGene, involving 175,226 individuals. Independent genetic variants associated with neuroticism and frailty were selected as instrumental variables. Inverse variance weighted (IVW), MR-Egger, weighted median, weighted mode, and MR-PRESSO were mainly used for MR analysis.

RESULTS

The MR analysis showed a positive causal relationship between neuroticism and the risk of frailty (odds ratio (OR) = 1.627, 95% confidence interval (CI) = 1.538-1.722, P < 0.001). In the reverse direction, frailty had a causal effect on a higher risk of neuroticism (OR = 1.270, 95% CI = 1.173-1.375, P < 0.001). Steiger tests indicated that reverse causation did not bias the identified causal relationships.

CONCLUSIONS

Our study provides genetic evidence suggesting a bi-directional causal relationship between frailty and neuroticism. In this bi-directional MR study, there were positive causal relationships between neuroticism-related phenotypes and frailty, and in the reverse direction, frailty was also positively correlated with neuroticism.

Unraveling the genetic susceptibility of irritable bowel syndrome: integrative genome-wide analyses in 845 492 individuals: a diagnostic study

BACKGROUND

Irritable bowel syndrome (IBS) significantly impacts individuals due to its prevalence and negative effect on quality of life. Current genome-wide association studies (GWAS) have only identified a small number of crucial single nucleotide polymorphisms (SNPs), not fully elucidating IBS's pathogenesis.

OBJECTIVE

To identify genomic loci at which common genetic variation influences IBS susceptibility.

METHODS

Combining independent cohorts that in total comprise 65 840 cases of IBS and 788 652 controls, the authors performed a meta-analysis of genome-wide association studies (GWAS) of IBS. The authors also carried out gene mapping and pathway enrichment to gain insights into the underlying genes and pathways through which the associated loci contribute to disease susceptibility. Furthermore, the authors performed transcriptome analysis to deepen their understanding. IBS risk models were developed by combining clinical/lifestyle risk factors with polygenic risk scores (PRS) derived from the GWAS meta-analysis. The authors detect the phenotype association for IBS utilizing PRS-based phenome-wide association (PheWAS) analyses, linkage disequilibrium score regression, and Mendelian randomization.

RESULTS

The GWAS meta-analysis identified 10 IBS risk loci, seven of which were novel (rs12755507, rs34209273, rs34365748, rs67427799, rs2587363, rs13321176, rs1546559). Multiple methods identified nine promising IBS candidate gene ( PRRC2A, COP1, CADM2, LRP1B, SUGT1, MED12L, P2RY14, PHF2, SHISA6 ) at 10 GWAS loci. Transcriptome validation also revealed differential expression of these genes. Phenome-wide associations between PRS-IBS and nine traits (neuroticism, diaphragmatic hernia, asthma, diverticulosis, cholelithiasis, depression, insomnia, COPD, and BMI) were identified. The six diseases (asthma, diaphragmatic hernia, diverticulosis, insomnia major depressive disorder and neuroticism) were found to show genetic association with IBS and only major depressive disorder and neuroticism were found to show causality with IBS.

CONCLUSION

The authors identified seven novel risk loci for IBS and highlighted the substantial influence on genetic risk harbored. The authors' findings offer novel insights into etiology and phenotypic association of IBS and lay the foundation for therapeutic targets and interventional strategies.

Mood instability and risk of gastrointestinal diseases - a univariable and multivariable mendelian randomization study

BACKGROUND

Mood instability, characterized by sudden and unpredictable mood shifts, is prevalent in psychiatric disorders and as a personality trait. Its association with gastrointestinal diseases has been recognized but remains poorly understood in terms of causality.

METHODS

This study aims to investigate the causal relationship between mood instability and a spectrum of gastrointestinal diseases by univariable and multivariable mendelian randomization analysis. The exposure and outcome data were retrieved from the IEU open GWAS database, the UK biobank and the FinnGen study. Instrumental variables were selected to meet relevance, independence, and exclusion restriction criteria. GWAS datasets for mood instability and 28 gastrointestinal diseases were utilized, incorporating diverse populations and genders. Univariable and multivariable Mendelian randomization analyses were conducted using R software. MR statistics from different datasets for the same disease were meta-analyzed to maximize the study population.

RESULTS

In univariable MR analysis, genetic predisposition to mood instability showed significant associations with increased risk for several gastrointestinal diseases, including: gastroesophageal reflux disease, gastric ulcer, acute gastritis, irritable bowel syndrome, internal hemorrhoids, cirrhosis, cholecystitis, cholelithiasis, acute pancreatitis, chronic pancreatitis. In multivariable MR analysis, after adjusting for major depression, bipolar disorder, anxiety disorder, and schizophrenia, associations with the following gastrointestinal diseases remained statistically significant: internal hemorrhoids, cirrhosis, acute pancreatitis, chronic pancreatitis.

CONCLUSION

This study provides compelling evidence for a potential causal relationship between mood instability and certain gastrointestinal diseases underscoring the importance of considering mood instability as a potential risk factor for gastrointestinal diseases as well as the positive role of maintaining mood stability in the prevention of gastrointestinal disorders.

Causal relationships between depression, emotional changes, and hiatal hernia: A Mendelian randomization analysis

Hiatal hernia (HH) is a common gastrointestinal disorder characterized by the displacement of abdominal contents, particularly the stomach, into the thoracic cavity. This condition is frequently associated with gastroesophageal reflux disease (GERD) and can lead to various symptoms, including chronic cough and respiratory issues. Despite its prevalence, the mechanisms linking psychological factors to HH are not well understood. Observational studies have suggested correlations between mental health issues - such as stress, anxiety, and depression - and gastrointestinal disorders, indicating that emotional states may influence the development of HH. This study aims to clarify the causal relationships between mood swings, depression, and the risk of developing HH using Mendelian randomization (MR), a robust method that utilizes genetic variants as instrumental variables (IVs) to infer causality. Data for this MR analysis were obtained from publicly available genome-wide association studies (GWAS). We employed a bidirectional, 2-sample MR approach, using IVs associated with mood swings, depression, feelings of tension, and feelings of misery as exposures, with HH as the outcome. A reverse MR analysis was also conducted, treating HH as the exposure and the aforementioned emotional states as outcomes. The primary analytical method used was inverse variance weighting (IVW), supplemented by sensitivity analyses, including MR-Egger and weighted median methods. Our analysis revealed significant associations: mood swings (OR = 1.014; 95% CI = 1.001-1.027; P = .032), depression (OR = 1.019; 95% CI = 1.006-1.033; P = .003), feelings of tension (OR = 1.012; 95% CI = 1.004-1.020; P = .001), and feelings of misery (OR = 1.007; 95% CI = 1.003-1.010; P = .0001) significantly increased the risk of HH. Importantly, reverse MR analysis indicated no causal influence of HH on these emotional states. This study provides evidence that mood swings, depression, feelings of tension, and feelings of misery are significant risk factors for developing HH. These findings highlight the need to address psychological factors in the clinical management and prevention strategies for HH, potentially improving patient outcomes.

A multi-regional human brain atlas of chromatin accessibility and gene expression facilitates promoter-isoform resolution genetic fine-mapping

Brain region- and cell-specific transcriptomic and epigenomic features are associated with heritability for neuropsychiatric traits, but a systematic view, considering cortical and subcortical regions, is lacking. Here, we provide an atlas of chromatin accessibility and gene expression profiles in neuronal and non-neuronal nuclei across 25 distinct human cortical and subcortical brain regions from 6 neurotypical controls. We identified extensive gene expression and chromatin accessibility differences across brain regions, including variation in alternative promoter-isoform usage and enhancer-promoter interactions. Genes with distinct promoter-isoform usage across brain regions were strongly enriched for neuropsychiatric disease risk variants. Moreover, we built enhancer-promoter interactions at promoter-isoform resolution across different brain regions and highlighted the contribution of brain region-specific and promoter-isoform-specific regulation to neuropsychiatric disorders. Including promoter-isoform resolution uncovers additional distal elements implicated in the heritability of diseases, thereby increasing the power to fine-map risk genes. Our results provide a valuable resource for studying molecular regulation across multiple regions of the human brain and underscore the importance of considering isoform information in gene regulation.

Genetic evidence for the causal association of neuroticism with intracranial aneurysms: A Mendelian randomization study

OBJECTIVE

The aim of this study was to assess the potential causal relationship between neuroticism and 12 neuroticism items with intracranial aneurysms (IAs) and aneurysmal subarachnoid hemorrhage (aSAH) using a two-sample Mendelian randomization (MR) approach.

METHODS

Study data were obtained from the Genome-Wide Association Study (GWAS) pooled dataset, and we extracted summary statistics for neuroticism, 12 neuroticism items, and IAs, which were categorized into ruptured and unruptured aneurysms (IA), aSAH, and unruptured IAs (uIA). Single nucleotide polymorphisms (SNPs) were used as instrumental variables (IVs) to explore the causal relationship between exposure and outcome using five Mendelian randomization methods, with Inverse variance weighted (IVW) as the primary study method. Horizontal multiple validity tests, sensitivity analyses, and inverse MR ensured the stability of the results.

RESULTS

The two-sample MR showed a genetically predictive association between neuroticism and IA [odds ratio (OR) = 1.16; 95 % confidence interval (95 % CI): 1.04-1.30; p = 0.009], aSAH (OR = 1.17; 95 % CI: 1.03-1.33; p = 0.013) and uIA (OR = 1.30; 95 % CI: 1.07-1.59; p = 0.009) were all genetically predictive of association. Ivw showed a positive association between 5 neuroticism items and IA risk, 5 neuroticism items and aSAH risk as well as no genetically predictive association between neuroticism items and uIA. Sensitivity analysis and inverse MR confirmed the robustness of the results.

CONCLUSION

Our Mendelian randomization analysis demonstrated genetic causality between neuroticism and neuroticism items with intracranial aneurysms, aneurysmal subarachnoid hemorrhage, and unruptured intracranial aneurysms, and further studies are needed to confirm these results and explore potential mechanisms of action.

Transcriptomic diversity of amygdalar subdivisions across humans and nonhuman primates

The amygdaloid complex mediates learning, memory, and emotions. Understanding the cellular and anatomical features that are specialized in the amygdala of primates versus other vertebrates requires a systematic, anatomically-resolved molecular analysis of constituent cell populations. We analyzed five nuclear subdivisions of the primate amygdala with single-nucleus RNA sequencing in macaques, baboons, and humans to examine gene expression profiles for excitatory and inhibitory neurons and confirmed our results with single-molecule FISH analysis. We identified distinct subtypes of FOXP2 + interneurons in the intercalated cell masses and protein-kinase C-δ interneurons in the central nucleus. We also establish that glutamatergic, pyramidal-like neurons are transcriptionally specialized within the basal, lateral, or accessory basal nuclei. Understanding the molecular heterogeneity of anatomically-resolved amygdalar neuron types provides a cellular framework for improving existing models of how amygdalar neural circuits contribute to cognition and mental health in humans by using nonhuman primates as a translational bridge.

Genetic determinants of coping, resilience and self-esteem in schizophrenia suggest a primary role for social factors and hippocampal neurogenesis

Schizophrenia is a severe psychiatric disorder, associated with a reduction in life expectancy of 15-20 years. Available treatments are at least partially effective in most affected individuals, and personal resources such as resilience (successful adaptation despite adversity) and coping abilities (strategies used to deal with stressful or threatening situations), are important determinants of disease outcomes and long-term sustained recovery. Published findings support the existence of a genetic background underlying resilience and coping, with variable heritability estimates. However, genome-wide analyses concerning the genetic determinants of these personal resources, especially in the context of schizophrenia, are lacking. Here, we performed a genome-wide association study coupled with accessory analyses to investigate potential genetic determinants of resilience, coping and self-esteem in 490 schizophrenia patients. Results revealed a complex genetic background partly overlapping with that of neuroticism, worry and schizophrenia itself and support the importance of social aspects in shapingthese psychological constructs. Hippocampal neurogenesis and lipid metabolism appear to be potentially relevant biological underpinnings, and specific miRNAs such as miR-124 and miR-137 may warrant further studies as potential biomarkers. In conclusion, this study represents an important first step in the identification of genetic and biological correlates shaping resilience, coping resources and self-esteem in schizophrenia.

Genetic correlation between chronic sinusitis and autoimmune diseases

Objective

The association between autoimmune diseases and chronic rhinosinusitis in observational studies remains unclear. This study aimed to explore the genetic correlation between chronic rhinosinusitis and autoimmune diseases.

Methods

We employed Mendelian randomization (MR) analysis and linkage disequilibrium score regression (LDSC) to investigate causal relationships and genetic correlations between autoimmune phenotypes and chronic rhinosinusitis. Additionally, transcriptome-wide association (TWAS) analysis was conducted to identify the shared genes between the two conditions to demonstrate their relationship. The CRS GWAS (genome-wide association study) data and other autoimmune diseases were retrieved from ieuOpenGWAS (https://gwas.mrcieu.ac.uk/), the FinnGen alliance (https://r8.finngen.fi/), the UK Biobank (https://www.ukbiobank.ac.uk/), and the EBI database (https://www.ebi.ac.uk/).

Results

Utilizing a bivariate two-sample Mendelian randomization approach, our findings suggest a significant association of chronic rhinosinusitis with various autoimmune diseases, including allergic rhinitis (p = 9.55E-10, Odds Ratio [OR] = 2,711.019, 95% confidence interval [CI] = 261.83391-28,069.8), asthma (p = 1.81E-23, OR = 33.99643, 95%CI = 17.52439-65.95137), rheumatoid arthritis (p = 9.55E-10, OR = 1.115526, 95%CI = 1.0799484-1.1522758), hypothyroidism (p = 2.08828E-2, OR = 4.849254, 95%CI = 1.7154455-13.707962), and type 1 diabetes (p = 2.08828E-2, OR = 01.04849, 95%CI = 1.0162932-1.0817062). LDSC analysis revealed a genetic correlation between the positive autoimmune phenotypes mentioned above and chronic rhinosinusitis: AR (rg = 0.344724754, p = 3.94E-8), asthma (rg = 0.43703672, p = 1.86E-10), rheumatoid arthritis (rg = 0.27834931, p = 3.5376E-2), and hypothyroidism (rg = -0.213201473, p = 3.83093E-4). Utilizing the Transcriptome-Wide Association Studies (TWAS) approach, we identified several genes commonly associated with both chronic rhinosinusitis and autoimmune diseases. Genes such as TSLP/WDR36 (Chromosome 5, top SNP: rs1837253), ORMDL3 (Chromosome 13, top SNP: rs11557467), and IL1RL1/IL18R1 (Chromosome 2, top SNP: rs12905) exhibited a higher degree of consistency in their shared involvement across atopic dermatitis (AT), allergic rhinitis (AR), and chronic rhinosinusitis (CRS).

Conclusion

Current evidence suggests a genetic correlation between chronic rhinosinusitis and autoimmune diseases like allergic rhinitis, asthma, rheumatoid arthritis, hypothyroidism, and type 1 diabetes. Further research is required to elucidate the mechanisms underlying these associations.

Genetics of cell-type-specific post-transcriptional gene regulation during human neurogenesis

The function of some genetic variants associated with brain-relevant traits has been explained through colocalization with expression quantitative trait loci (eQTL) conducted in bulk postmortem adult brain tissue. However, many brain-trait associated loci have unknown cellular or molecular function. These genetic variants may exert context-specific function on different molecular phenotypes including post-transcriptional changes. Here, we identified genetic regulation of RNA editing and alternative polyadenylation (APA) within a cell-type-specific population of human neural progenitors and neurons. More RNA editing and isoforms utilizing longer polyadenylation sequences were observed in neurons, likely due to higher expression of genes encoding the proteins mediating these post-transcriptional events. We also detected hundreds of cell-type-specific editing quantitative trait loci (edQTLs) and alternative polyadenylation QTLs (apaQTLs). We found colocalizations of a neuron edQTL in CCDC88A with educational attainment and a progenitor apaQTL in EP300 with schizophrenia, suggesting that genetically mediated post-transcriptional regulation during brain development leads to differences in brain function.

Oxygen-induced stress reveals context-specific gene regulatory effects in human brain organoids

The interaction between genetic variants and environmental stressors is key to understanding the mechanisms underlying neurological diseases. In this study, we used human brain organoids to explore how varying oxygen levels expose context-dependent gene regulatory effects. By subjecting a genetically diverse panel of 21 brain organoids to hypoxic and hyperoxic conditions, we identified thousands of gene regulatory changes that are undetectable under baseline conditions, with 1,745 trait-associated genes showing regulatory effects only in response to oxygen stress. To capture more nuanced transcriptional patterns, we employed topic modeling, which revealed context-specific gene regulation linked to dynamic cellular processes and environmental responses, offering a deeper understanding of how gene regulation is modulated in the brain. These findings underscore the importance of genotype-environment interactions in genetic studies of neurological disorders and provide new insights into the hidden regulatory mechanisms influenced by environmental factors in the brain.

Genetic causality between modifiable risk factors and the risk of rheumatoid arthritis: Evidence from Mendelian randomization

OBJECTIVES

Emerging research has investigated the potential impact of several modifiable risk factors on the risks of rheumatoid arthritis (RA), but the findings did not yield consistent results. This study aimed to comprehensively explore the genetic causality between modifiable risk factors and the susceptibility of RA risk using the Mendelian randomization (MR) approach.

METHODS

Genetic instruments for modifiable risk factors were selected from several genome-wide association studies at the genome-wide significance level (p < 5 × 10-8), respectively. Summary-level data for RA were sourced from a comprehensive meta-analysis. The causal estimates linking modifiable risk factors to RA risk were assessed using MR analysis with inverse variance weighting (IVW), MR-Egger, weighted, and weighted median methods.

RESULTS

After Bonferroni correction for multiple tests, we found the presence of causality between educational attainment and RA, where there were protective effects of educational attainment (college completion) (odds ratio [OR] = 0.50, 95% CI = 0.36, 0.69, p = 2.87E-05) and educational attainment (years of education) (OR = 0.93, 95% CI = 0.90, 0.96, p = 4.18E-06) on the lower RA risks. Nevertheless, smoking initiation was observed to be associated with increased RA risks (OR = 1.27, 95% CI = 1.09, 1.47, p = .002). Moreover, there was no indication of horizontal pleiotropy of genetic variants during causal inference between modifiable risk factors and RA.

CONCLUSIONS

Our study reveals the genetic causal impacts of educational attainment and smoking on RA risks, suggesting that the early monitoring and recognition of modifiable risk factors would be beneficial for the preventive counseling/treatment strategies for RA.

A Two-Sample Mendelian Randomization Study of Neuroticism and Sleep Bruxism

Sleep bruxism (SB) affects a considerable part of the population and is associated with neuroticism, stress, and anxiety in various studies. However, the causal mechanisms between neuroticism and SB have not been examined. Understanding the reasons for SB is important as understanding bruxism may allow improved comprehensive management of the disorders and comorbidities related to it. Previous studies on the association of risk factors to SB have provided important symptomatic insight but were mainly questionnaire based or limited in sample size and could not adequately assess causal relationships. The aim of this study was to elaborate the possible causal relationship of neuroticism as a risk factor for SB through a Mendelian randomization (MR) approach by combining questionnaires, registry data, and genetic information in large scale. We performed a two-sample MR study using instrumental genetic variants of neuroticism, including neuroticism subcategories, in the UK Biobank (n = 380,506) and outcome data of probable SB using FinnGen (n [cases/controls] = 12,297/364,980). We discovered a causal effect from neuroticism to SB (odds ratio [OR] = 1.38 [1.10-1.74], P = 0.0057). A phenotype sensitive to stress and adversity had the strongest effect (OR = 1.59 [1.17-2.15], P = 0.0028). Sensitivity analyses across MR methods supported a causal relationship, and we did not observe pleiotropy between neuroticism and SB (MR-Egger intercept, P = 0.87). Our findings are in line with earlier observational studies that connect stress and SB. Furthermore, our results provide evidence that neurotic traits increase the risk of probable SB.

Associations Between a General Factor and Group Factor from the Spanish-Language Eysenck Personality Questionnaire-Revised Short Form's Neuroticism Scale and the Revised NEO Personality Inventory Domains and Facets

Prior studies used exploratory bifactor analyses to examine the structure of the Neuroticism scale from the Short-scale Eysenck Personality Questionnaire-Revised (EPQ-RS). These studies revealed a general factor and two group factors-Anxious-Tense and Worried-Vulnerable. These factors were related to poorer mental health, but their associations with physical health differed, as did their genetic and neurobiological underpinnings. A later study found that their associations with the Big Five Inventory-2 Short Form's factors and facets differed. We reanalyzed data on 1,006 Spanish students who completed Spanish-language versions of the EPQ-RS and the Revised NEO Personality Inventory (NEO PI-R). Using confirmatory factor analysis, we showed that a model comprising the general factor and a group factor-Anxious-Tense-fit well. In later correlations, a joint factor analysis, and simultaneous multiple regressions, we showed that the EPQ-RS's general factor and the group factor had different patterns of associations with the NEO PI-R domains and facets. These associations were consistent with the definition of the EPQ-RS Neuroticism scale's general factor and that of the group factor. Further investigation into the EPQ-RS Neuroticism scale's structure can improve our understanding of neuroticism's relationship with health and other outcomes.

A Novel Detection Method for High-Order SNP Epistatic Interactions Based on Explicit-Encoding-Based Multitasking Harmony Search

To elucidate the genetic basis of complex diseases, it is crucial to discover the single-nucleotide polymorphisms (SNPs) contributing to disease susceptibility. This is particularly challenging for high-order SNP epistatic interactions (HEIs), which exhibit small individual effects but potentially large joint effects. These interactions are difficult to detect due to the vast search space, encompassing billions of possible combinations, and the computational complexity of evaluating them. This study proposes a novel explicit-encoding-based multitasking harmony search algorithm (MTHS-EE-DHEI) specifically designed to address this challenge. The algorithm operates in three stages. First, a harmony search algorithm is employed, utilizing four lightweight evaluation functions, such as Bayesian network and entropy, to efficiently explore potential SNP combinations related to disease status. Second, a G-test statistical method is applied to filter out insignificant SNP combinations. Finally, two machine learning-based methods, multifactor dimensionality reduction (MDR) as well as random forest (RF), are employed to validate the classification performance of the remaining significant SNP combinations. This research aims to demonstrate the effectiveness of MTHS-EE-DHEI in identifying HEIs compared to existing methods, potentially providing valuable insights into the genetic architecture of complex diseases. The performance of MTHS-EE-DHEI was evaluated on twenty simulated disease datasets and three real-world datasets encompassing age-related macular degeneration (AMD), rheumatoid arthritis (RA), and breast cancer (BC). The results demonstrably indicate that MTHS-EE-DHEI outperforms four state-of-the-art algorithms in terms of both detection power and computational efficiency. The source code is available at https://github.com/shouhengtuo/MTHS-EE-DHEI.git .

Genetic factors and symptom dimensions associated with antidepressant treatment outcomes: clues for new potential therapeutic targets?

Treatment response and resistance in major depressive disorder (MDD) show a significant genetic component, but previous studies had limited power also due to MDD heterogeneity. This literature review focuses on the genetic factors associated with treatment outcomes in MDD, exploring their overlap with those associated with clinically relevant symptom dimensions. We searched PubMed for: (1) genome-wide association studies (GWASs) or whole exome sequencing studies (WESs) that investigated efficacy outcomes in MDD; (2) studies examining the association between MDD treatment outcomes and specific depressive symptom dimensions; and (3) GWASs of the identified symptom dimensions. We identified 13 GWASs and one WES of treatment outcomes in MDD, reporting several significant loci, genes, and gene sets involved in gene expression, immune system regulation, synaptic transmission and plasticity, neurogenesis and differentiation. Nine symptom dimensions were associated with poor treatment outcomes and studied by previous GWASs (anxiety, neuroticism, anhedonia, cognitive functioning, melancholia, suicide attempt, psychosis, sleep, sociability). Four genes were associated with both treatment outcomes and these symptom dimensions: CGREF1 (anxiety); MCHR1 (neuroticism); FTO and NRXN3 (sleep). Other overlapping signals were found when considering genes suggestively associated with treatment outcomes. Genetic studies of treatment outcomes showed convergence at the level of biological processes, despite no replication at gene or variant level. The genetic signals overlapping with symptom dimensions of interest may point to shared biological mechanisms and potential targets for new treatments tailored to the individual patient's clinical profile.

Unique genetic and risk-factor profiles in clusters of major depressive disorder-related multimorbidity trajectories

The heterogeneity and complexity of symptom presentation, comorbidities and genetic factors pose challenges to the identification of biological mechanisms underlying complex diseases. Current approaches used to identify biological subtypes of major depressive disorder (MDD) mainly focus on clinical characteristics that cannot be linked to specific biological models. Here, we examined multimorbidities to identify MDD subtypes with distinct genetic and non-genetic factors. We leveraged dynamic Bayesian network approaches to determine a minimal set of multimorbidities relevant to MDD and identified seven clusters of disease-burden trajectories throughout the lifespan among 1.2 million participants from cohorts in the UK, Finland, and Spain. The clusters had clear protective- and risk-factor profiles as well as age-specific clinical courses mainly driven by inflammatory processes, and a comprehensive map of heritability and genetic correlations among these clusters was revealed. Our results can guide the development of personalized treatments for MDD based on the unique genetic, clinical and non-genetic risk-factor profiles of patients.

Impact of gene-by-trauma interaction in MDD-related multimorbidity clusters

BACKGROUND

Major depressive disorder (MDD) is considerably heterogeneous in terms of comorbidities, which may hamper the disentanglement of its biological mechanism. In a previous study, we classified the lifetime trajectories of MDD-related multimorbidities into seven distinct clusters, each characterized by unique genetic and environmental risk-factor profiles. The current objective was to investigate genome-wide gene-by-environment (G × E) interactions with childhood trauma burden, within the context of these clusters.

METHODS

We analyzed 77,519 participants and 6,266,189 single-nucleotide polymorphisms (SNPs) of the UK Biobank database. Childhood trauma burden was assessed using the Childhood Trauma Screener (CTS). For each cluster, Plink 2.0 was used to calculate SNP × CTS interaction effects on the participants' cluster membership probabilities. We especially focused on the effects of 31 candidate genes and associated SNPs selected from previous G × E studies for childhood maltreatment's association with depression.

RESULTS

At SNP-level, only the high-multimorbidity Cluster 6 revealed a genome-wide significant SNP rs145772219. At gene-level, MPST and PRH2 were genome-wide significant for the low-multimorbidity Clusters 1 and 3, respectively. Regarding candidate SNPs for G × E interactions, individual SNP results could be replicated for specific clusters. The candidate genes CREB1, DBH, and MTHFR (Cluster 5) as well as TPH1 (Cluster 6) survived multiple testing correction.

LIMITATIONS

CTS is a short retrospective self-reported measurement. Clusters could be influenced by genetics of individual disorders.

CONCLUSIONS

The first G × E GWAS for MDD-related multimorbidity trajectories successfully replicated findings from previous G × E studies related to depression, and revealed risk clusters for the contribution of childhood trauma.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis-regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

Causality between Sarcopenia and Depression: A Bidirectional Mendelian Randomization Study

BACKGROUND

Numerous observational studies have suggested a correlation between sarcopenia and depression, but the nature of this relationship requires further investigation.

METHODS

This study employed bidirectional Mendelian randomization to explore this connection. Data from genome-wide association studies were used, encompassing measures of sarcopenia and mental factors, including depression and emotional states. The initial analysis concentrated on the impact of depression on sarcopenia, and then it examined the reverse relationship. The same methodology was applied to emotional data for validation.

RESULTS

The results indicated a reciprocal causation between sarcopenia and depression, even when emotional state data were considered. Various emotions can impact sarcopenia, and in turn, sarcopenia can affect emotions, except subjective well-being. These findings highlight a cyclic deterioration between sarcopenia and depression, with a link to negative emotions and a partially ameliorative effect of subjective well-being on sarcopenia.

CONCLUSIONS

In summary, this study sheds light on the interplay between psychiatric factors and sarcopenia, offering insights into intervention and prevention strategies.

Activation of the interleukin-23/Th17 axis in major depression: a systematic review and meta-analysis

The interleukin-23/Th17 axis is a promising modifiable target for depression. However, its association with depression has not been systematically evaluated. We systematically searched four databases (EMBASE, Web of Science, Pubmed and PsycINFO) for studies comparing patients with major depression and healthy controls for plasma/serum levels of Th17 cells and their canonical cytokines (interleukin-17A [IL-17A], IL-22, granulocyte macrophage colony stimulating factor [GM-CSF]). We also compared counts of Th1, Th2 and Th9 cells between depressed/non-depressed patients and their respective canonical cytokines. We performed random-effects meta-analysis of the standardised mean difference (SMD) in immune measures between groups. Risk of bias was assessed using the Newcastle-Ottawa scale. Of 3154 studies screened, 36 studies were included in meta-analysis. Patients with depression had elevated IL-17A compared to controls (SMD = 0.80 [95% CI 0.03 to 1.58], p = 0.042), an association moderated by antidepressant use (Z = 2.12, p = 0.034). Patients with depression had elevated GM-CSF (SMD = 0.54 [95% CI 0.16 to 0.91], p = 0.0047), and a trend towards higher Th17 counts (SMD = 0.44 [- 0.01 to 0.88], p = 0.052). Whilst the Th2-associated cytokine IL-5 was elevated in depression (SMD = 0.36 [95% CI 0.05 to 0.66], p = 0.02), Th2 cell counts (p = 0.97), Th1 cell counts (p = 0.17) and interferon-γ (p = 0.22) were not. Data for Th9 cells, IL-9 and IL-22 were insufficient for meta-analysis. Respectively, 22, 25 and 5 studies were good, fair and poor in quality. Patients with major depression show peripheral over-activation of the IL-23/Th17 axis. Future interventional studies should test whether this is a modifiable target for depression.

Impact of negative emotions on upper gastrointestinal diseases: A Mendel randomization study

Mendelian randomization method is a powerful tool in epidemiological research. The core idea is to use genetic variation as a tool to assess the causal relationship between risk factors and specific diseases. Confounding factors are important interference factors for causal inference in epidemiological studies, and genetic variation in Mendelian randomization studies follows the principle of random distribution of alleles to offspring, which is similar to randomized controlled trials. Mendel 's randomization method can effectively avoid the confounding factors, reverse causality in observational studies and the representativeness and feasibility of randomized controlled trials. Previous observational studies have reported a relationship between negative emotions and upper gastrointestinal disease. However, whether this relationship is causal remains unclear. We aimed to evaluate the causal relationship between negative emotions and upper gastrointestinal diseases using two-sample Mendelian randomization (MR). Three sets of genetic instruments from the database were obtained for analysis, including 12 anxiety-related single nucleotide polymorphisms (SNPs), 46 depression-related SNPs, and 58 nervous-related SNPs. SNPs were filtered using the Phenoscanner website, and the inverse variance weighted method, weighted median method, MR-Egger regression, MR pleiotropy residual sum, and outlier test were used for analysis. In inverse variance weighted analysis, anxiety and depression had an effect on gastroduodenal ulcer (p = 2.849×10-3, β = 4.908, 95% CI = 1.684-8.132; and p = 6.457×10-4, β = 1.767, 95% CI = 0.752-2.782, respectively). Additionally, depression had an effect on diseases of the esophagus, stomach, and duodenum (p = 3.498×10-5, β = 0.926, 95% CI = 0.487-1.364). Cochran's Q-derived p-values were 0.457, 0.603, and 0.643, and MR-Egger intercept-derived p-values were 0.697, 0.294, and 0.362, respectively. Here, we show that anxiety and depression have a causal relationship with gastroduodenal ulcers, and depression has a causal relationship with diseases of the esophagus, stomach, and duodenum.

Genetic Correlates of Treatment-Resistant Depression: Insights from Polygenic Scores Across Cognitive, Temperamental, and Sleep Traits in the All of US cohort

Background

Treatment-resistant depression (TRD) is a major challenge in mental health, affecting a significant number of patients and leading to considerable economic and social burdens. The etiological factors contributing to TRD are complex and not fully understood.

Objective

To investigate the genetic factors associated with TRD using polygenic scores (PGS) across various traits, and to explore their potential role in the etiology of TRD using large-scale genomic data from the All of Us Research Program (AoU).

Methods

Data from 292,663 participants in the AoU were analyzed using a case-cohort design. Treatment resistant depression (TRD), treatment responsive Major Depressive Disorder (trMDD), and all others who have no formal diagnosis of Major Depressive Disorder (non-MDD) were identified through diagnostic codes and prescription patterns. Polygenic scores (PGS) for 61 unique traits from seven domains were used and logistic regressions were conducted to assess associations between PGS and TRD. Finally, Cox proportional hazard models were used to explore the predictive value of PGS for progression rate from the diagnostic event of Major Depressive Disorder (MDD) to TRD.

Results

In the discovery set (104128 non-MDD, 16640 trMDD, and 4177 TRD), 44 of 61 selected PGS were found to be significantly associated with MDD, regardless of treatment responsiveness. Eleven of them were found to have stronger associations with TRD than with trMDD, encompassing PGS from domains in education, cognition, personality, sleep, and temperament. Genetic predisposition for insomnia and specific neuroticism traits were associated with increased TRD risk (OR range from 1.05 to 1.15), while higher education and intelligence scores were protective (ORs 0.88 and 0.91, respectively). These associations are consistent across two other independent sets within AoU (n = 104,388 and 63,330). Among 28,964 individuals tracked over time, 3,854 developed TRD within an average of 944 days (95% CI: 883 ~ 992 days) after MDD diagnosis. All eleven previously identified and replicated PGS were found to be modulating the conversion rate from MDD to TRD. Thus, those having higher education PGS would experiencing slower conversion rates than those who have lower education PGS with hazard ratios in 0.79 (80th versus 20th percentile, 95% CI: 0.74 ~ 0.85). Those who had higher insomnia PGS experience faster conversion rates than those who had lower insomnia PGS, with hazard ratios in 1.21 (80th versus 20th percentile, 95% CI: 1.13 ~ 1.30).

Conclusions

Our results indicate that genetic predisposition related to neuroticism, cognitive function, and sleep patterns play a significant role in the development of TRD. These findings underscore the importance of considering genetic and psychosocial factors in managing and treating TRD. Future research should focus on integrating genetic data with clinical outcomes to enhance our understanding of pathways leading to treatment resistance.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis- regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

Shared and Unique Genetic Links between Neuroticism and Gastrointestinal Tract Diseases

Objective

Association between neuroticism and gastrointestinal tract (GIT) diseases may not be attributable to the genetic overlaps between neuroticism and psychiatric disorders. We aim to explore the genetic links and mechanisms of neuroticism and GIT diseases.

Materials and Methods

We obtained European genome-wide association data of neuroticism (n = 390,278) or subclusters (depressed, n = 357,957; worry, n = 348,219) and six GIT diseases: gastroesophageal reflux disease (GERD, n = 456,327), inflammatory bowel disease (IBD, n = 456,327), peptic ulcer disease (PUD, n = 456,327), irritable bowel syndrome (IBS, n = 486,601), Crohn's disease (CD, n = 20,883), and ulcerative colitis (UC, n = 21,895). We performed genetic correlation analysis (high-definition likelihood method and cross-trait linkage disequilibrium score regression), pairwise pleiotropic analysis, single nucleic acid polymorphism annotation, Bayesian colocalization, gene-level analysis, transcriptome-wide association analysis, and gene set enrichment analysis.

Results

Neuroticism and its subclusters are associated with most GIT diseases (15 of 18 trait-pairs). GERD and PUD were highly correlated with depressed affect. We identified pleiotropic loci 11q23.2 (mapped gene: NCAM1/DRD2) and 18q12.2 (mapped gene: CELF4) in neuroticism and IBS/GERD, supporting the genetic overlap between neuroticism and depression. We found that 16q12.1 (mapped gene: NKD1/ZNF423/NOD2) and 2q37.1 (mapped gene: ATG16L1/SP140) are only highlighted in depressed/neuroticism CD, revealing pleiotropic loci with dissimilarities between neuroticism and different GIT diseases. MR analysis suggested that genetic liability to neuroticism is associated with increased risks of IBS, PUD, and GERD.

Conclusion

Our findings document the genetic links between neuroticism and six GIT diseases, highlighting the genetic overlaps and heterogeneity between neuroticism and psychiatric disorders in the context of gastrointestinal disorders. Both the shared and unique pleiotropic loci identified between neuroticism and different GIT diseases could facilitate mechanistic understandings and may stimulate further translational implications.

Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals

Cannabis is one of the most widely used drugs globally. Decriminalization of cannabis is further increasing cannabis consumption. We performed genome-wide association studies (GWASs) of lifetime (N=131,895) and frequency (N=73,374) of cannabis use. Lifetime cannabis use GWAS identified two loci, one near CADM2 (rs11922956, p=2.40E-11) and another near GRM3 (rs12673181, p=6.90E-09). Frequency of use GWAS identified one locus near CADM2 (rs4856591, p=8.10E-09; r2 =0.76 with rs11922956). Both traits were heritable and genetically correlated with previous GWASs of lifetime use and cannabis use disorder (CUD), as well as other substance use and cognitive traits. Polygenic scores (PGSs) for lifetime and frequency of cannabis use associated cannabis use phenotypes in AllofUs participants. Phenome-wide association study of lifetime cannabis use PGS in a hospital cohort replicated associations with substance use and mood disorders, and uncovered associations with celiac and infectious diseases. This work demonstrates the value of GWASs of CUD transition risk factors.

Genome-wide association studies (GWAS) and post-GWAS analyses of impulsivity: A systematic review

Impulsivity is related to a host of mental and behavioral problems. It is a complex construct with many different manifestations, most of which are heritable. The genetic compositions of these impulsivity manifestations, however, remain unclear. A number of genome-wide association studies (GWAS) and post-GWAS analyses have tried to address this issue. We conducted a systematic review of all GWAS and post-GWAS analyses of impulsivity published up to December 2023. Available data suggest that single nucleotide polymorphisms (SNPs) in more than a dozen of genes (e.g., CADM2, CTNNA2, GPM6B) are associated with different measures of impulsivity at genome-wide significant levels. Post-GWAS analyses further show that different measures of impulsivity are subject to different degrees of genetic influence, share few genetic variants, and have divergent genetic overlap with basic personality traits such as extroversion and neuroticism, cognitive ability, psychiatric disorders, substance use, and obesity. These findings shed light on controversies in the conceptualization and measurement of impulsivity, while providing new insights on the underlying mechanisms that yoke impulsivity to psychopathology.

Genetic and phenotypic heterogeneity in early neurodevelopmental traits in the Norwegian Mother, Father and Child Cohort Study

BACKGROUND

Autism and different neurodevelopmental conditions frequently co-occur, as do their symptoms at sub-diagnostic threshold levels. Overlapping traits and shared genetic liability are potential explanations.

METHODS

In the population-based Norwegian Mother, Father, and Child Cohort study (MoBa), we leverage item-level data to explore the phenotypic factor structure and genetic architecture underlying neurodevelopmental traits at age 3 years (N = 41,708-58,630) using maternal reports on 76 items assessing children's motor and language development, social functioning, communication, attention, activity regulation, and flexibility of behaviors and interests.

RESULTS

We identified 11 latent factors at the phenotypic level. These factors showed associations with diagnoses of autism and other neurodevelopmental conditions. Most shared genetic liabilities with autism, ADHD, and/or schizophrenia. Item-level GWAS revealed trait-specific genetic correlations with autism (items rg range = - 0.27-0.78), ADHD (items rg range = - 0.40-1), and schizophrenia (items rg range = - 0.24-0.34). We find little evidence of common genetic liability across all neurodevelopmental traits but more so for several genetic factors across more specific areas of neurodevelopment, particularly social and communication traits. Some of these factors, such as one capturing prosocial behavior, overlap with factors found in the phenotypic analyses. Other areas, such as motor development, seemed to have more heterogenous etiology, with specific traits showing a less consistent pattern of genetic correlations with each other.

CONCLUSIONS

These exploratory findings emphasize the etiological complexity of neurodevelopmental traits at this early age. In particular, diverse associations with neurodevelopmental conditions and genetic heterogeneity could inform follow-up work to identify shared and differentiating factors in the early manifestations of neurodevelopmental traits and their relation to autism and other neurodevelopmental conditions. This in turn could have implications for clinical screening tools and programs.

Causal effects of childhood obesity on neuroticism and subjective well-being: A two-sample Mendelian randomization study

BACKGROUND

Childhood obesity is linked to both neuroticism and subjective wellbeing (SWB); however, the causal relations between them remain unclear.

METHODS

Two-sample Mendelian randomization (MR) analysis was applied to determine the causal effects of childhood BMI (n = 39,620) on neuroticism (n = 366,301) and SWB (n = 298,420) using summary statistics from large scale genome-wide association studies (GWASs). Inverse-variance weighting (IVW), weighted mode, weighted median, and MR-Egger approaches were used to estimate the causal effects. Sensitivity analyses including the Cochran's Q statistics, MR-Egger intercept test, MR-PRESSO global test, and the leave-one-out (LOO) analysis were used to assess potential heterogeneity and horizontal pleiotropy. Two-step MR mediation analysis was employed to explore the potential mediation effects of neuroticism on the causal relationship between childhood BMI and SWB.

RESULTS

Our study revealed that genetically predicted higher childhood BMI was causally associated with increased neuroticism (beta = 0.045, 95%CI = 0.013,0.077, p = 6.066e-03) and reduced SWB (beta = -0.059, 95%CI = -0.093,-0.024, p = 9.585e-04). Sensitivity analyses didn't detect any significant heterogeneity and horizontal pleiotropy (all p > 0.05). Additionally, the two-step MR mediation analysis indicated that the causal relationship between childhood BMI and SWB was partially mediated by neuroticism (proportion of mediation effects in total effects: 21.3 %, 95%CI: 5.4 % to 37.2, p = 0.0088).

CONCLUSION

Genetically proxy for higher childhood BMI was associated with increased neuroticism and reduced SWB. Further studies were warranted to investigate the underlying molecular mechanisms and potential use of weight management for improving personality and SWB.

Large-scale whole-exome sequencing of neuropsychiatric diseases and traits in 350,770 adults

While numerous genomic loci have been identified for neuropsychiatric conditions, the contribution of protein-coding variants has yet to be determined. Here we conducted a large-scale whole-exome-sequencing study to interrogate the impact of protein-coding variants on 46 neuropsychiatric diseases and 23 traits in 350,770 adults from the UK Biobank. Twenty new genes were associated with neuropsychiatric diseases through coding variants, among which 16 genes had impacts on the longitudinal risks of diseases. Thirty new genes were associated with neuropsychiatric traits, with SYNGAP1 showing pleiotropic effects across cognitive function domains. Pairwise estimation of genetic correlations at the coding-variant level highlighted shared genetic associations among pairs of neurodegenerative diseases and mental disorders. Lastly, a comprehensive multi-omics analysis suggested that alterations in brain structures, blood proteins and inflammation potentially contribute to the gene-phenotype linkages. Overall, our findings characterized a compendium of protein-coding variants for future research on the biology and therapeutics of neuropsychiatric phenotypes.

Genetically predicted mood swings increased risk of cardiovascular disease: Evidence from a Mendelian randomization analysis

BACKGROUND

Mood swings is linked to a higher risk of cardiovascular diseases (CVDs). However, the causal relationships between them remain unknown.

METHODS

We conducted this Mendelian randomization (MR) analysis to evaluate the causal associations between mood swings (n = 373,733) and 5 CVDs, including CAD, MI, HF, AF, and stroke using summary data of large-scale genome-wide association studies (GWAS). FinnGen datasets validated the results. Various MR approaches, sensitivity analyses, multivariable MR (MVMR), and two-step MR mediation analyses were applied.

RESULTS

The MR analysis revealed significant causal effects of mood swings on CAD (OR = 1.45, 95 % CI 1.24-1.71; P = 5.52e-6), MI (OR = 1.60, 95 % CI 1.32-1.95; P = 1.77e-6), HF (OR = 1.42, 95 % CI 1.18-1.71; P = 2.32e-4), and stroke (OR = 1.48, 95 % CI 1.19-1.83; P = 3.46e-4), excluding AF (P = 0.16). In the reverse MR analysis, no causal relationships were observed. The results were reproducible using FinnGen data. In the MVMR analysis, the causal effects of mood swings on CAD, MI, HF and stroke still remain significant after adjusting potential confounding factors including BMI, smoking and T2DM, but not for LDL and hypertension. Further mediation analysis indicated hypertension may mediate the causal pathways from mood swings to CAD (18.11 %, 95 % CI: 8.83 %-27.39 %), MI (16.40 %, 95 % CI: 7.93 %-24.87 %), HF (13.06 %, 95 % CI: 6.25 %-19.86 %), and stroke (18.04 %, 95 % CI: 8.73 %-27.34 %).

CONCLUSION

Mood swings has a significant causal impact on the development of CAD, MI, HF, and stroke, partly mediated by hypertension.

Shared genetics linking sociability with the brain's default mode network

The brain's default mode network (DMN) plays a role in social cognition, with altered DMN function being associated with social impairments across various neuropsychiatric disorders. In the present study, we examined the genetic relationship between sociability and DMN-related resting-state functional magnetic resonance imaging (rs-fMRI) traits. To this end, we used genome-wide association summary statistics for sociability and 31 activity and 64 connectivity DMN-related rs-fMRI traits (N=34,691-342,461). First, we examined global and local genetic correlations between sociability and the rs-fMRI traits. Second, to assess putatively causal relationships between the traits, we conducted bi-directional Mendelian randomisation (MR) analyses. Finally, we prioritised genes influencing both sociability and rs-fMRI traits by combining three methods: gene-expression eQTL MR analyses, the CELLECT framework using single-nucleus RNA-seq data, and network propagation in the context of a protein-protein interaction network. Significant local genetic correlations were found between sociability and two rs-fMRI traits, one representing spontaneous activity within the temporal cortex, the other representing connectivity between the frontal/cingulate and angular/temporal cortices. Sociability affected 12 rs-fMRI traits when allowing for weakly correlated genetic instruments. Combing all three methods for gene prioritisation, we defined 17 highly prioritised genes, with DRD2 and LINGO1 showing the most robust evidence across all analyses. By integrating genetic and transcriptomics data, our gene prioritisation strategy may serve as a blueprint for future studies. The prioritised genes could be explored as potential biomarkers for social dysfunction in the context of neuropsychiatric disorders and as drug target genes.