Meta-analysis of genome-wide association studies of anxiety disorders

Polygenic dissection of treatment-resistant depression with proxy phenotypes in the UK Biobank

BACKGROUND

Treatment-resistant depression (TRD) affects one-third of major depressive disorder (MDD) patients. Previous pharmacogenetic studies suggest genetic variation may influence medication response but findings are heterogeneous. We conducted a comprehensive genetic investigation using proxy TRD phenotypes (TRDp) that mirror the treatment options of MDD from UK Biobank primary care records.

METHODS

Among 15,125 White British MDD patients, we identified TRDp with medication changes (switching or receiving multiple antidepressants [AD]); augmentation therapy (antipsychotics; mood stabilizers; valproate; lithium); or electroconvulsive therapy (ECT). Hospitalized TRDp patients (HOSP-TRDp) were also identified. We conducted genome-wide association analysis, estimated SNP-heritability (hg2), and assessed the genetic burden for nine psychiatric diseases using polygenic risk scores (PRS).

RESULTS

TRDp patients were more often female, unemployed, less educated, and had higher BMI, with hospitalization rates twice as high as non-TRDp. While no credible risk variants emerged, heritability analysis showed significant genetic influence on TRDp (liability hg2 21-24 %), particularly for HOSP-TRDp (28-31 %). TRDp classified by AD changes and augmentation carried an elevated yet varied polygenic burden for MDD, ADHD, BD, and SCZ. Higher BD PRS increased the likelihood of receiving ECT, lithium, and valproate by 1.27-1.80 fold. Patients in the top 10 % PRS relative to the average had a 12-36 % and 24-51 % higher risk of TRDp and HOSP-TRDp, respectively.

CONCLUSIONS

Our findings support a significant polygenic basis for TRD, highlighting genetic and phenotypic distinctions from non-TRD. We demonstrate that different TRDp endpoints are enriched with various spectra of psychiatric genetic liability, offering insights into pharmacogenomics and TRD's complex genetic architecture.

Genetic insights into the role of mitochondria-related genes in mental disorders: An integrative multi-omics analysis

BACKGROUND

Mitochondrial dysfunction has been implicated in the development of mental disorders, yet the underlying mechanisms remain unclear. In this study, we employed summary-data-based Mendelian randomization (SMR) analysis to explore the associations between mitochondrial-related genes and seven common mental disorders across gene expression, DNA methylation, and protein levels.

METHOD

Summary statistics from genome-wide association studies were used for seven mental disorders, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, anxiety, bipolar disorder, major depressive disorder, post-traumatic stress disorder, and schizophrenia (SCZ). Instrumental variables associated with 1136 mitochondria-related genes were derived from summary statistics for DNA methylation, gene expression, and protein quantitative trait loci. SMR analyses and colocalization analyses were then conducted across these three biological levels to explore the associations with each of the seven mental disorders.

RESULTS

We identified mitochondria-related genes associated with mental disorders with multi-omics evidence: RMDN1 for ADHD, and ACADVL, ETFA, MMAB, and PPA2 for SCZ. Specifically, an increase of one standard deviation in the level of RMDN1 was linked to a 12 % decrease in the risk of developing ADHD (OR = 0.88, 95 % CI: 0.83-0.94). Increased levels of ETFA (OR = 1.79, 95 % CI: 1.24-2.60) and MMAB (OR = 1.10, 95 % CI: 1.05-1.16) were significantly associated with increased risk of SCZ. Conversely, high levels of ACADVL (OR = 0.50, 95 % CI: 0.33-0.77) and PPA2 (OR = 0.68, 95 % CI: 0.55-0.85) were associated with a reduced risk of SCZ.

CONCLUSIONS

These findings suggested that dysfunction in mitochondria-related genes may underlie the molecular mechanisms of ADHD and SCZ, providing novel biomarkers for diagnosis and therapeutic interventions.

Exploring the association between urticaria subtypes, anxiety, and depression and potential role of gut microbiota

AIMS

In observational studies, the causal relationship between urticaria and the risk of psychiatric disorders (anxiety and depression) remains inconclusive. Furthermore, there is growing evidence that gut microbiota (GM) contributes to the pathogenesis of urticaria. This study aimed to assess the causal relationships between the genetically predicted urticaria subtypes and psychiatric disorders and further examined the role of GM in influencing the risk of these urticaria subtypes.

METHODS

We conducted a meta-analysis of observational studies identified from four databases to evaluate the associations between urticaria, anxiety, and depression over the past decade. In addition, we estimated the genetic correlation and causality between genetically predicted urticaria subtypes and psychiatric disorders using linkage disequilibrium score regression and Mendelian Randomization (MR) analyses. Finally, univariable two-sample MR and multivariable MR analyses were employed to evaluate the combined and independent effects of GM from two datasets on urticaria subtypes associated with psychiatric disorders.

RESULTS

Thirteen observational studies comprising 7321 participants were included in the meta-analysis. There was a positive association between urticaria and anxiety risk (n = 13, OR: 3.96; 95%CI: 2.90-5.41) as well as depression risk (n = 12, OR: 3.03; 95%CI: 2.30-4.01). The MR results indicated that idiopathic urticaria increased the risk of anxiety (OR = 1.14; 95%CI = 1.01-1.28; P = 3.31 × 10-2), while allergic urticaria increased the risk of major depressive disorder (OR = 1.07; 95%CI = 1.02-1.13; P = 6.65 × 10-3). Our analysis identified nineteen gut bacterial taxa that were causally associated with idiopathic and allergic urticaria. Notably, Intestinibacter and Victivallales were strongly associated with an increased risk of allergic urticaria, even after accounting for the effect of smoking or alcohol consumption in the multivariable MR analysis. FamilyXIIIAD3011group and Bacteroides vulgatus were found to exert protective roles in idiopathic urticaria.

CONCLUSIONS

The study provides evidence for the association between urticaria subtypes and psychiatric disorders, complementing existing observational studies. In addition, our study implies the involvement of gut microbiota in idiopathic and allergic urticaria. However, the specific mechanisms of bacterial action remain to be clarified.

Enhancing the discriminatory power of polygenic scores for ADHD and autism in clinical and non-clinical samples

BACKGROUND

Polygenic scores (PGS) are widely used in psychiatric genetic associations studies due to their predictive power for focal outcomes. However, they lack discriminatory power, in part due to the high degree of genetic overlap between psychiatric disorders. The lack of prediction specificity limits the clinical utility of psychiatric PGS, particularly for diagnostic applications. The goal of the study was to enhance the discriminatory power of psychiatric PGS for two highly comorbid and genetically correlated neurodevelopmental disorders in ADHD and autism spectrum disorder (ASD).

METHODS

Genomic structural equation modeling (GenomicSEM) was used to generate novel PGS for ADHD and ASD by accounting for the genetic overlap between these disorders (and eight others) to achieve greater discriminatory power in non-focal outcome predictions. PGS associations were tested in two large independent samples - the Philadelphia Neurodevelopmental Cohort (N = 4,789) and the Simons Foundation Powering Autism Research for Knowledge (SPARK) ASD and sibling controls (N = 5,045) cohort.

RESULTS

PGS from GenomicSEM achieved superior discriminatory power in terms of showing significantly attenuated associations with non-focal outcomes relative to traditionally computed PGS for these disorders. Additionally, genetic correlations between GenomicSEM PGS for ASD and ADHD were significantly attenuated in cross-trait associations with other psychiatric disorders and outcomes.

CONCLUSIONS

Psychiatric PGS associations are likely inflated by the high degree of genetic overlap between the psychiatric disorders. Methods such as GenomicSEM can be used to refine PGS signals to be more disorder-specific, thereby enhancing their discriminatory power for future diagnostic applications.

Genetic liability for anxiety and treatment response to the monoamine stabilizer OSU6162 in alcohol dependence: a retrospective secondary analysis

BACKGROUND

OSU6162, a monoamine stabilizer, has demonstrated efficacy in reducing alcohol and anxiety-related behaviors in preclinical settings. In a previous randomized, double-blind, placebo-controlled trial involving patients with alcohol dependence (AD), OSU6162 significantly reduced craving for alcohol but did not alter drinking behaviors. This retrospective secondary analysis explores whether genetic predispositions related to AD and associated traits might influence the response to OSU6162 treatment in original trial participants.

METHODS

Polygenic risk scores (PRSs) were calculated for 48 AD patients using PRSice-2 and genome-wide association study (GWAS) data for (i) alcohol use disorder and alcohol consumption, (ii) problematic alcohol use, (iii) drinks per week, (iv) major depression, and (v) anxiety (case-control comparisons and quantitative anxiety factor scores). Linear regression analyses, adjusted for population stratification, assessed interaction effects between PRSs and treatment type (OSU6162 or placebo) on various clinical outcomes.

RESULTS

Significant interactions were found between treatment type and anxiety factor score PRS at the genome-wide significance threshold. In the OSU6162-treated group, a higher anxiety PRS was associated with reductions in the number of drinks consumed (FDR = 0.0017), percentage of heavy drinking days (FDR = 0.0060), and percentage of drinking days (FDR = 0.0017), with a trend toward reduced blood phosphatidylethanol (PEth) levels (FDR = 0.068). These associations were absent in the placebo group.

CONCLUSIONS

These preliminary findings suggest that anxiety PRS may help predict response to OSU6162 treatment in AD. Further research with larger cohorts and more comprehensive genetic data is needed to confirm these results and advance personalized medicine approaches for alcohol use disorder.

Genomics of Anxiety Disorders

Anxiety disorders are the most prevalent psychiatric conditions in the general population. Despite the early observation of family aggregation of anxiety disorders with a heritability of 30% to 50%, their exact genetic structure is not yet determined. Evidence suggests a composition of common and rare genetic factors contributing to the etiology of anxiety disorders. Recent hypothesis-free genome-wide association studies in mega cohorts mostly with a broad anxiety phenotype rendered an increasing number of novel genetic loci. Epigenetic research is still in its infancy with first evidence showing dynamic changes in response to environmental influences and during the therapy course.

Causal relationships between depression, anxiety, and myopia: a two-sample Mendelian randomization study

OBJECTIVES

To investigate the causal relationship between depression, anxiety, and myopia.

METHODS

The multivariable Mendelian randomization (MR) design using summary statistics from independent genome-wide association studies (GWAS) was employed. The anxiety and depression, were used as exposures, and myopia was used as the outcome. Genetic variants associated with depression were derived using GWAS summary statistics from the FinnGen consortium database. Genetic variants associated with anxiety were derived from the Psychiatric Genomics consortium. The inverse-variance-weighted method was the main applied analytic tool and was complemented with comprehensive sensitivity analyses.

RESULTS

A total of 21, 10 SNPs were selected as instrumental variables for depression and anxiety, respectively. Based on the IVW analysis, both depression (OR = 1.010, 95% CI = 1.002-1.018, P = 0.016) and anxiety (OR = 1.083, 95%CI = 1.022-1.149, P = 0.008) increased the risk of myopia. After adjusting in the multivariable MR, the IVW and Egger methods indicated that depression (OR = 1.004, 95%CI = 1.000-1.008, P = 0.030) or anxiety (OR = 1.004, 95%CI = 1.001-1.008, P = 0.026) was still associated with elevated risks of myopia.

CONCLUSIONS

The current study identified a causal relationship between anxiety, depression, and an increased risk of myopia. These observations suggest that when developing strategies to control myopia, it is also important to focus on the mental health of children. Further detailed research is needed to fully understand this issue.

Contributions of common and rare genetic variation to different measures of mood and anxiety disorder in the UK Biobank

BACKGROUND

Mood and anxiety disorders co-occur and share symptoms, treatments and genetic risk, but it is unclear whether combining them into a single phenotype would better capture genetic variation. The contribution of common genetic variation to these disorders has been investigated using a range of measures; however, the differences in their ability to capture variation remain unclear, while the impact of rare variation is mostly unexplored.

AIMS

We aimed to explore the contributions of common genetic variation and copy number variations associated with risk of psychiatric morbidity (P-CNVs) to different measures of internalising disorders.

METHOD

We investigated eight definitions of mood and anxiety disorder, and a combined internalising disorder, derived from self-report questionnaires, diagnostic assessments and electronic healthcare records (EHRs). Association of these definitions with polygenic risk scores (PRSs) of major depressive disorder and anxiety disorder, as well as presence of a P-CNV, was assessed.

RESULTS

The effect sizes of both PRSs and P-CNVs were similar for mood and anxiety disorder. Compared to mood and anxiety disorder, internalising disorder resulted in higher prediction accuracy for PRSs, and increased significance of associations with P-CNVs for most definitions. Comparison across the eight definitions showed that PRSs had higher prediction accuracy and effect sizes for stricter definitions, whereas P-CNVs were more strongly associated with EHR- and self-report-based definitions.

CONCLUSIONS

Future studies may benefit from using a combined internalising disorder phenotype, and may need to consider that different phenotype definitions may be more informative depending on whether common or rare variation is studied.

Integrating HiTOP and RDoC frameworks Part I: Genetic architecture of externalizing and internalizing psychopathology

BACKGROUND

There is considerable comorbidity between externalizing (EXT) and internalizing (INT) psychopathology. Understanding the shared genetic underpinnings of these spectra is crucial for advancing knowledge of their biological bases and informing empirical models like the Research Domain Criteria (RDoC) and Hierarchical Taxonomy of Psychopathology (HiTOP).

METHODS

We applied genomic structural equation modeling to summary statistics from 16 EXT and INT traits in individuals genetically similar to European reference panels (EUR-like; n = 16,400 to 1,074,629). Traits included clinical (e.g. major depressive disorder, alcohol use disorder) and subclinical measures (e.g. risk tolerance, irritability). We tested five confirmatory factor models to identify the best fitting and most parsimonious genetic architecture and then conducted multivariate genome-wide association studies (GWAS) of the resulting latent factors.

RESULTS

A two-factor correlated model, representing EXT and INT spectra, provided the best fit to the data. There was a moderate genetic correlation between EXT and INT (r = 0.37, SE = 0.02), with bivariate causal mixture models showing extensive overlap in causal variants across the two spectra (94.64%, SE = 3.27). Multivariate GWAS identified 409 lead genetic variants for EXT, 85 for INT, and 256 for the shared traits.

CONCLUSIONS

The shared genetic liabilities for EXT and INT identified here help to characterize the genetic architecture underlying these frequently comorbid forms of psychopathology. The findings provide a framework for future research aimed at understanding the shared and distinct biological mechanisms underlying psychopathology, which will help to refine psychiatric classification systems and potentially inform treatment approaches.

Transdiagnostic and Disorder-Level GWAS Enhance Precision of Substance Use and Psychiatric Genetic Risk Profiles in African and European Ancestries

BACKGROUND

Substance use disorders (SUDs) and psychiatric disorders frequently co-occur, and their etiology likely reflects both transdiagnostic (i.e., common/shared) and disorder-level (i.e., independent/nonshared) genetic influences. Understanding the genetic influences that are shared and those that operate independently of the shared risk could enhance precision in diagnosis, prevention, and treatment, but this remains underexplored, particularly in non-European ancestry groups.

METHODS

We applied genomic structural equation modeling to examine the common and independent genetic architecture among SUDs and psychotic, mood, and anxiety disorders using summary statistics from genome-wide association studies (GWAS) conducted in European- (EUR) and African-ancestry (AFR) individuals. To characterize the biological and phenotypic associations, we used FUMA, conducted genetic correlations, and performed phenome-wide association studies (PheWAS).

RESULTS

In EUR individuals, transdiagnostic genetic factors represented SUDs, psychotic, and mood/anxiety disorders, with GWAS identifying two novel lead single-nucleotide polymorphisms (SNPs) for the mood factor. In AFR individuals, genetic factors represented SUDs and psychiatric disorders, and GWAS identified one novel lead SNP for the SUD factor. In EUR individuals, second-order factor models showed phenotypic and genotypic associations with a broad range of physical and mental health traits. Finally, genetic correlations and PheWAS highlighted how common and independent genetic factors for SUD and psychotic disorders were differentially associated with psychiatric, sociodemographic, and medical phenotypes.

CONCLUSIONS

Combining transdiagnostic and disorder-level genetic approaches can improve our understanding of co-occurring conditions and increase the specificity of genetic discovery, which is critical for identifying more effective prevention and treatment strategies to reduce the burden of these disorders.

Analysis of gut microbiota and depression and anxiety: Mendelian randomization from three datasets

BACKGROUND

Emerging evidence supports gut microbiota's association with mental distress, particularly depression and anxiety, the microbiota-gut-brain axis was the believed to be the underlying mechanism. This study investigated the causal relationships between specific gut microbiota and depression and anxiety disorders using large-scale genome-wide association study (GWAS) data.

METHODS

A two-sample bidirectional Mendelian randomization (MR) analysis was conducted to explore the causal effects of 211 microbial taxa on depression and anxiety across three large GWAS databases: FinnGen, Pan-UKBB, and PGC. Sensitive analyses were followed to validate the robustness of results. Random-effect meta-analysis was further performed to enhance the statistical power.

RESULTS

The MR analysis revealed that the Bifidobacteriales (IVW: OR 0.90, 95 %CI 0.83 to 0.98) and Bifidobacteriaceae (IVW: OR 0.90, 95 %CI 0.83 to 0.98) had a protective effect against depression. Clostridiales (cML-MA: OR 0.88, 95 %CI 0.81 to 0.95) and Parasutterella (cML-MA: OR 0.75, 95 %CI 0.64 to 0.88) showed negative associations with depression. Increased abundance of Oxalobacteraceae (cML-MA: OR 1.78, 95 %CI 1.24 to 2.56), Deltaproteobacteria (cML-MA: OR 2.17, 95 %CI 1.38 to 3.40), and Desulfovibrionales (cML-MA: OR 2.22, 95 %CI 1.41 to 3.49) was associated with a higher risk of depression. For anxiety, protective effects were found for Actinobacteria (phylum: IVW: OR 0.83, 95 %CI 0.76 to 0.87; class: IVW: OR 0.84, 95 %CI 0.75 to 0.93), Bifidobacteriales (IVW: OR 0.80, 95 %CI 0.75 to 0.85), Bifidobacteriaceae (IVW: OR 0.80, 95 %CI 0.75 to 0.85) and Bifidobacterium [g] (IVW: OR 0.79, 95 %CI 0.74 to 0.84). Lactobacillaceae [f] (cML-MA: OR 1.18, 95 %CI 1.08 to 1.28), Clostridia [c] (cML-MA: OR 1.15, 95 %CI 0.1.06 to 1.26) and Clostridiales [o] (IVW: OR 1.15, 95 %CI 1.05 to 1.27) were associated with increased anxiety risk. Meta-analysis results indicated significant associations, particularly the protective effects of Actinobacteria (OR 0.90, 95 % CI, 0.83 to 0.98) and Clostridiaceae1 (OR 0.91, 95 % CI, 0.83 to 0.99) on depression and several taxa on anxiety. No significant instrumental variables for depression or anxiety on gut microbiota were identified.

CONCLUSIONS

Our findings highlight specific gut microbiota that are associated with depression and anxiety, underscoring the causal relationships between these intestinal microbes and psychiatric disorders. These results suggest potential strategies for mitigating disease symptoms and improving quality of life through microbiome-targeted therapies. Further studies, including randomized controlled trials and investigations into sex-specific effects, are essential to validate and expand upon these findings.

Causal relationship between graves' disease and mental disorders: A bidirectional Mendelian randomization study

OBJECTIVE

Many patients with Graves' disease (GD) also suffer from mental disorders in clinical practice, but their causal relationship remains unclear. This study aims to investigate the causal relationship between GD and common mental disorders using a bidirectional Mendelian randomization (MR)approach.

METHODS

We derived genome-wide association study (GWAS) data for common mental disorders, including major depressive disorder (MDD), anxiety disorders, bipolar disorder, and attention-deficit/hyperactivity disorder (ADHD), from the Psychiatric Genomics Consortium consortium. GWAS data for GD were obtained from the FinnGen consortium. Subsequently, a bidirectional MR analysis was conducted, with the inverse-variance weighted (IVW) methods as the primary MR analysis method. Sensitivity analysis used Cochran's Q test, MR-Egger intercept test, and leave-one-out method.

RESULTS

IVW results in MR demonstrated a positive association between genetic susceptibility to GD and bipolar disorder (OR = 1.073, 95 % CI: 1.042-1.105, p = 2.882 × 10-6). Similar causal estimates were obtained through MR-Egger regression and the weighted median method. Additionally, both Cochran's Q test and MR-Egger intercept test indicated no evidence of heterogeneity or pleiotropy. However, no causal associations were demonstrated between GD and MDD, anxiety disorders, or ADHD. Furthermore, a causal relationship between genetic susceptibility to common mental disorders and GD was not evidenced.

CONCLUSIONS

This bidirectional MR study supports the role of GD in the causal association with an increased risk of bipolar disorder, which guides us to pay attention to the mental diseases of GD patients in the clinic.

Immunological drivers and potential novel drug targets for major psychiatric, neurodevelopmental, and neurodegenerative conditions

Immune dysfunction is implicated in the aetiology of psychiatric, neurodevelopmental, and neurodegenerative conditions, but the issue of causality remains unclear impeding attempts to develop new interventions. Using genomic data on protein and gene expression across blood and brain, we assessed evidence of a potential causal role for 736 immune response-related biomarkers on 7 neuropsychiatric conditions by applying Mendelian randomization (MR) and genetic colocalisation analyses. A systematic three-tier approach, grouping biomarkers based on increasingly stringent criteria, was used to appraise evidence of causality (passing MR sensitivity analyses, colocalisation, False Discovery Rate and Bonferroni thresholds). We provide evidence for a potential causal role of 29 biomarkers for 7 conditions. The identified biomarkers suggest a role of both brain specific and systemic immune response in the aetiology of schizophrenia, Alzheimer's disease, depression, and bipolar disorder. Of the identified biomarkers, 20 are therapeutically tractable, including ACE, TNFRSF17, SERPING1, AGER and CD40, with drugs currently approved or in advanced clinical trials. Based on the largest available selection of plasma immune-response related biomarkers, our study provides insight into possible influential biomarkers for the aetiology of neuropsychiatric conditions. These genetically prioritised biomarkers now require examination to further evaluate causality, their role in the aetiological mechanisms underlying the conditions, and therapeutic potential.

Epigenetic markers of disease risk and psychotherapy response in anxiety disorders - a longitudinal analysis of the DNA methylome

Epigenetic mechanisms such as DNA methylation are hypothesized to play a pivotal role in the pathogenesis of anxiety disorders and to predict as well as relate to treatment response. An epigenome-wide association study (EWAS) (Illumina MethylationEPIC BeadChip) was performed at baseline (BL), post-treatment (POST) and 6-month follow-up (FU) in the so far largest longitudinal sample of patients with anxiety disorders (N = 415) treated with exposure-based cognitive behavioral therapy (CBT), and in 315 healthy controls. Independent of comorbidity with depression, anxiety disorders were significantly (p ≤ 6.409E-08) associated with altered DNA methylation at 148 CpGs partly mapping to genes previously implicated in processes related to anxiety, brain disorders, learning or plasticity (e.g., GABBR2, GABRD, GAST, IL12RB2, LINC00293, LOC101928626, MFGE8, NOTCH4, PTPRN2, RIMBP2, SPTBN1) or in a recent cross-anxiety disorders EWAS (TAOK1) after pre-processing and quality control (N = 378 vs. N = 295). Furthermore, BL DNA methylation at seven and three CpGs, respectively, was suggestively (p < 1E-5) associated with treatment response at POST (ABCA7, ADRA2C, LTBR, RPSAP52, SH3RF3, SLC47A2, ZNF251) and FU (ADGRD1, PRSS58, USP47). Finally, suggestive evidence for dynamic epigenome-wide DNA methylation changes along with CBT response emerged at four CpGs from BL to FU (ADIPOR2, EIF3B, OCA2, TMCC1). The identification of epigenetic biomarkers may eventually aid in developing environment-based preventive strategies aimed at increasing resilience by providing deeper molecular insights into the mechanisms underlying anxiety disorders. Defining epigenetic signatures as predictors or key mechanisms in exposure-based interventions could pave the way for more targeted and personalized treatments for anxiety disorders.

Cardiovascular diseases and depression: A meta-analysis and Mendelian randomization analysis

Depression is a common psychiatric symptom among patients with cardiovascular disease (CVD), adversely affecting their health. Despite the identification of various contributing factors, the precise mechanisms linking CVD and depression remain elusive. This study conducted a meta-analysis to investigate the association between CVD and depression. Furthermore, a bidirectional Mendelian randomization (MR) analysis was undertaken to clarify the causal relationship between the two conditions. The meta-analysis included 39 studies, encompassing 63,444 patients with CVD, 12,308 of whom were diagnosed with depression. The results revealed a significant association between CVD and depression or anxiety, with an estimated overall prevalence of depression in CVD patients of 20.8%. Subgroup analyses showed that the prevalence of depression in patients with coronary artery disease and heart failure was 19.8% and 24.7%, respectively. According to a random-effects model, depressive symptoms were linked to an increase in unadjusted all-cause mortality compared with non-depressed patients. The MR analysis, employing the inverse-variance weighted method as the primary tool for causality assessment, identified significant associations between various CVD types and depression or anxiety phenotypes. These findings underscore the significant relationship between CVD and depression or anxiety, leading to an elevated risk of all-cause mortality. Moreover, the MR analysis provides the first genetically-informed evidence suggesting that depression plays a critical role in the development and progression of certain CVD subtypes. This emphasizes the need for addressing depressive symptoms in CVD patients to prevent or reduce adverse cardiovascular outcomes.

White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life

Advanced diffusion magnetic resonance imaging (dMRI) allows one to probe and assess brain white matter (WM) organisation and microstructure in vivo. Various dMRI models with different theoretical and practical assumptions have been developed, representing partly overlapping characteristics of the underlying brain biology with potentially complementary value in the cognitive and clinical neurosciences. To which degree the different dMRI metrics relate to clinically relevant geno- and phenotypes is still debated. Hence, we investigate how tract-based and whole WM skeleton parameters from different dMRI approaches associate with clinically relevant and white matter-related phenotypes (sex, age, pulse pressure (PP), body-mass-index (BMI), brain asymmetry) and genetic markers in the UK Biobank (UKB, n=52,140) and the Adolescent Brain Cognitive Development (ABCD) Study (n=5,844). In general, none of the imaging approaches could explain all examined phenotypes, though the approaches were overall similar in explaining variability of the examined phenotypes. Nevertheless, particular diffusion parameters of the used dMRI approaches stood out in explaining some important phenotypes known to correlate with general human health outcomes. A multi-compartment Bayesian dMRI approach provided the strongest WM associations with age, and together with diffusion tensor imaging, the largest accuracy for sex-classifications. We find a similar pattern of metric and tract-dependent asymmetries across datasets, with stronger asymmetries in ABCD data. The magnitude of WM associations with polygenic scores as well as PP depended more on the sample, and likely age, than dMRI metrics. However, kurtosis was most indicative of BMI and potentially of bipolar disorder polygenic scores. We conclude that WM microstructure is differentially associated with clinically relevant pheno- and genotypes at different points in life.

Cross-Sectional Brain Age Assessments Are Limited in Predicting Future Brain Change

The concept of brain age (BA) describes an integrative imaging marker of brain health, often suggested to reflect aging processes. However, the degree to which cross-sectional MRI features, including BA, reflect past, ongoing, and future brain changes across different tissue types from macro- to microstructure remains controversial. Here, we use multimodal imaging data of 39,325 UK Biobank participants, aged 44-82 years at baseline and 2,520 follow-ups within 1.12-6.90 years to examine BA changes and their relationship to anatomical brain changes. We find insufficient evidence to conclude that BA reflects the rate of brain aging. However, modality-specific differences in brain ages reflect the state of the brain, highlighting diffusion and multimodal MRI brain age as potentially useful cross-sectional markers.

Associations between multiple ambient air pollutants, genetic risk, and incident mental disorders: An interaction study in the UK population

Mental disorders can be triggered by genetic and environmental risk factors. Limited studies have explored the effects of long-term exposure to air pollution on mental disorders, and most of the studies have focused on individual air pollutants. This study aimed to examine the relationship between long-term exposure to multiple air pollutants and incident mental disorders, including depression, anxiety, and schizophrenia, and whether the associations were affected by genetic susceptibility. Participants in the UK Biobank with no history of mental disorders were followed from baseline (2006 to 2010) to October 31st, 2022. Cox regression was applied to evaluate the correlation between PM2.5 absorbance, PM2.5, PM2.5-10, PM10, NO2, and NOx and any or specific mental disorders. Additive and multiplicative scales were used to measure the interaction between air pollution and schizophrenia polygenic risk score (PRS), depression PRS, or anxiety PRS on specific mental diseases. After a median of 13.36 years of follow-up on 252,376 participants, we observed per interquartile increase of PM2.5 absorbance (0.32 per meter), PM2.5 (1.28 μg/m3), NO2 (10.08 μg/m3), and NOx (16.78 μg/m3) were related to a 2-6 % higher risk of incident mental disorders. The HR (95 % CI) of incident mental disorder for the 2nd, 3rd, and 4th quartile of the air pollution score were 1.05 (1.01-1.18), 1.13 (1.09-1.18), and 1.14 (1.09-1.19), respectively, in comparison to the lowest level of the score. Per interquartile increase in the air pollution score was associated with a 6 %, 24 %, 4 %, and 6 % higher risk of incident mental disorders, schizophrenia, depression, and anxiety, respectively. No interaction between air pollution and genetic risk of schizophrenia, depression or anxiety on corresponding incident disorders was observed. These findings emphasize the importance of implementing air pollution control standards to decrease the burden of mental disorders.

Psychiatric genetics in the diverse landscape of Latin American populations

Psychiatric disorders are highly heritable and polygenic, influenced by environmental factors and often comorbid. Large-scale genome-wide association studies (GWASs) through consortium efforts have identified genetic risk loci and revealed the underlying biology of psychiatric disorders and traits. However, over 85% of psychiatric GWAS participants are of European ancestry, limiting the applicability of these findings to non-European populations. Latin America and the Caribbean, regions marked by diverse genetic admixture, distinct environments and healthcare disparities, remain critically understudied in psychiatric genomics. This threatens access to precision psychiatry, where diversity is crucial for innovation and equity. This Review evaluates the current state and advancements in psychiatric genomics within Latin America and the Caribbean, discusses the prevalence and burden of psychiatric disorders, explores contributions to psychiatric GWASs from these regions and highlights methods that account for genetic diversity. We also identify existing gaps and challenges and propose recommendations to promote equity in psychiatric genomics.

Polygenic Risk Score Analysis of Antidepressant Treatment Outcomes: A CAN-BIND-1 Study Report: Analyse des résultats du traitement antidépresseur à l'aide des scores de risque polygéniques : Rapport sur l'étude CAN-BIND-1

ObjectiveThe genetic architecture of antidepressant response is poorly understood. This study investigated whether polygenic risk scores (PRSs) for major psychiatric disorders and a personality trait (neuroticism) are associated with antidepressant treatment outcomes.MethodsWe analysed 148 participants with major depressive disorder (MDD) from the Canadian Biomarker Integration Network for Depression-1 (CAN-BIND-1) cohort. Participants initially received escitalopram (ESC) monotherapy for 8 weeks. Nonresponders at week 8 received augmentation with aripiprazole (ARI), while responders continued ESC until week 16. Primary outcomes were remission status and symptom improvement measured at weeks 8 and 16. At week 16, post-hoc stratified analyses were performed by treatment arm (ESC-only vs. ESC + ARI). Eleven PRSs derived from genome-wide association studies of psychiatric disorders (e.g., MDD and post-traumatic stress syndrome (PTSD)) and neuroticism, were analysed for associations with these outcomes using logistic and linear regression models.ResultsAt week 8, a higher PRS for PTSD was nominally associated with a lower probability of remission (odds ratio (OR) = 0.08 [0.014-0.42], empirical p-value = 0.017) and reduced symptom improvement (beta (standard error) = -29.15 (9.76), empirical p-value = 0.019). Similarly, a higher PRS for MDD was nominally associated with decreased remission probability (OR = 0.38 [0.18-0.78], empirical p-value = 0.044). However, none of the results survived multiple testing corrections. At week 16, the stratified analysis for the ESC-only group revealed that a higher PRS for MDD was associated with increased remission probability (empirical p-value = 0.034) and greater symptom improvement (empirical p-value = 0.02). In contrast, higher PRSs for schizophrenia (empirical p-value = 0.013) and attention-deficit hyperactivity disorder (empirical p-value = 0.032) were associated with lower symptom improvement. No significant associations were observed in the ESC + ARI group.ConclusionsThese findings suggest that PRSs may influence treatment outcomes, particularly in ESC monotherapy. Replication in larger studies is needed to validate these observations.

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.

Transdiagnostic Polygenic Risk Models for Psychopathology and Comorbidity: Cross-Ancestry Analysis in the All of Us Research Program

Psychiatric disorders exhibit substantial genetic overlap, raising questions about the utility of transdiagnostic genetic risk models. Using data from the All of Us Research Program (N=102,091), we evaluated common psychiatric genetic (CPG) factor-based polygenic risk scores (PRSs) compared to standard disorder-specific PRSs. The CPG PRS consistently outperformed disorder-specific scores in predicting individual disorder risk, explaining 1.07 to 24.6 times more phenotypic variance across 11 psychiatric conditions. Meanwhile, many disorder-specific PRSs retained independent but smaller contributions, highlighting the complementary nature of shared and disorder-specific genetic risk. While alternative multi-factor models improved model fit, the CPG PRS provided comparable or superior predictive performance across most disorders, including overall comorbidity burden. Cross-ancestry analyses however revealed notable limitations of European-centric GWAS datasets for other populations due to ancestral differences in genetic architecture. These findings underscore the potential value of transdiagnostic PRSs for psychiatric genetics while highlighting the need for more equitable genetic risk models.

Causal Relationships Between Retinal Diseases and Psychiatric Disorders Have Implications for Precision Psychiatry

Observational studies and clinical trials have reported potential associations between retinal diseases and psychiatric disorders. However, the causal associations between them have remained elusive. In this study, we used bi-directional two-sample Mendelian randomization (MR) analysis to explore unconfounded causal relationships between retinal diseases and psychiatric disorders using large-scale genome-wide association study (GWAS) summary statistics of over 500,000 participants of European ancestry from the FinnGen project, the Psychiatric Genomics Consortium, the European Bioinformatics Institute, and the UK Biobank. Our MR analysis revealed significant causal relationships between major retinal diseases and specific psychiatric disorders. Specifically, susceptibility to dry age-related macular degeneration was associated with a reduced risk of anorexia nervosa (OR = 0.970; 95% CI = 0.930 ~ 0.994; P = 0.025). Furthermore, we found some evidence that exposure to diabetic retinopathy was associated with an increased risk of schizophrenia (OR = 1.021; 95% CI 1.012 ~ 1.049; P = 0.001), and exposure to retinal detachments and breaks was associated with an increased risk of attention deficit hyperactivity disorder (OR = 1.190; 95% CI 1.063 ~ 1.333; P = 0.003). These causal relationships were not confounded by biases of pleiotropy and reverse causation. Our study highlights the importance of preventing and managing retinal disease as a potential avenue for improving the prevention, management and treatment of major psychiatric disorders.

Integrating HiTOP and RDoC Frameworks Part I: Genetic Architecture of Externalizing and Internalizing Psychopathology

Background

There is considerable comorbidity between externalizing (EXT) and internalizing (INT) psychopathology. Understanding the shared genetic underpinnings of these spectra is crucial for advancing knowledge of their biological bases and informing empirical models like the Research Domain Criteria (RDoC) and Hierarchical Taxonomy of Psychopathology (HiTOP).

Methods

We applied genomic structural equation modeling to summary statistics from 16 EXT and INT traits in European-ancestry individuals (n = 16,400 to 1,074,629). Traits included clinical (e.g., major depressive disorder, alcohol use disorder) and subclinical measures (e.g., risk tolerance, irritability). We tested five confirmatory factor models to identify the best fitting and most parsimonious genetic architecture and then conducted multivariate genome-wide association studies (GWAS) of the resulting latent factors.

Results

A two-factor correlated model, representing EXT and INT spectra, provided the best fit to the data. There was a moderate genetic correlation between EXT and INT (r = 0.37, SE = 0.02), with bivariate causal mixture models showing extensive overlap in causal variants across the two spectra (94.64%, SE = 3.27). Multivariate GWAS identified 409 lead genetic variants for EXT, 85 for INT, and 256 for the shared traits.

Conclusions

The shared genetic liabilities for EXT and INT identified here help to characterize the genetic architecture underlying these frequently comorbid forms of psychopathology. The findings provide a framework for future research aimed at understanding the shared and distinct biological mechanisms underlying psychopathology, which will help to refine psychiatric classification systems and potentially inform treatment approaches.

Investigating shared risk variants and genetic etiology between Alzheimer's disease and three stress-related psychiatric disorders: a large-scale genome-wide cross-trait analysis

Introduction

Observational studies have reported that patients with Alzheimer's disease (AD) have a greater burden of comorbidities typically associated with stress-related psychiatric disorders. However, the contribution of hereditary factors to this comorbidity remains unclear. We evaluated phenotypic associations using observational data from the UK Biobank.

Method

Our study focused on investigating the shared risk variants and genetic etiology underlying AD and three stress-related psychiatric disorders: post-traumatic stress disorder, anxiety disorder, and major depressive disorder. By leveraging summary statistics from genome-wide association studies, we investigated global genetic correlations using linkage disequilibrium score regression, genetic covariance analysis, and high-definition likelihood. Genome-wide cross-trait analysis with association analysis based on subsets and cross-phenotype association were performed to discover genome-wide significant risk variants shared between AD and the three stress-related psychiatric disorders.

Results

A significant positive genetic correlation was observed between AD and major depressive disorder using linkage disequilibrium score regression (rg = 0.231; P = 0.018), genetic covariance analysis (rg = 0.138; P < 0.001), and high-definition likelihood (rg = 0.188; P < 0.001). Association analysis based on subsets and cross-phenotype association revealed thirteen risk variants in six genes shared between AD and post-traumatic stress disorder; seven risk variants in four genes shared between AD and anxiety disorder; and 23 risk variants in four genes shared between AD and major depressive disorder. Functional annotation and gene-set enrichment analysis indicated that 12 genes for comorbidity shared between patients with AD and all three stress-related psychiatric disorders were enriched in the spleen, pancreas, and whole blood.

Conclusion

These results advance our knowledge of the shared genetic origins of comorbidities and pave the way for advancements in the diagnosis, management, and prevention of stress-related AD.

Triangulated evidence provides no support for bidirectional causal pathways between diet/physical activity and depression/anxiety

BACKGROUND

Previous studies (various designs) present contradicting insights on the potential causal effects of diet/physical activity on depression/anxiety (and vice versa). To clarify this, we employed a triangulation framework including three methods with unique strengths/limitations/potential biases to examine possible bidirectional causal effects of diet/physical activity on depression/anxiety.

METHODS

Study 1: 3-wave longitudinal study (n = 9,276 Dutch University students). Using random intercept cross-lagged panel models to study temporal associations. Study 2: cross-sectional study (n = 341 monozygotic and n = 415 dizygotic Australian adult twin pairs). Using a co-twin control design to separate genetic/environmental confounding. Study 3: Mendelian randomization utilizing data (European ancestry) from genome-wide association studies (n varied between 17,310 and 447,401). Using genetic variants as instrumental variables to study causal inference.

RESULTS

Study 1 did not provide support for bidirectional causal effects between diet/physical activity and symptoms of depression/anxiety. Study 2 did provide support for causal effects between fruit/vegetable intake and symptoms of depression/anxiety, mixed support for causal effects between physical activity and symptoms of depression/anxiety, and no support for causal effects between sweet/savoury snack intake and symptoms of depression/anxiety. Study 3 provides support for a causal effect from increased fruit intake to the increased likelihood of anxiety. No support was found for other pathways. Adjusting the analyses including diet for physical activity (and vice versa) did not change the conclusions in any study.

CONCLUSIONS

Triangulating the evidence across the studies did not provide compelling support for causal effects of diet/physical activity on depression/anxiety or vice versa.

Casual associations between frailty and nine mental disorders: bidirectional Mendelian randomisation study

BACKGROUND

An increasing number of observational studies have reported associations between frailty and mental disorders, but the causality remains ambiguous.

AIMS

To assess the bidirectional causal relationship between frailty and nine mental disorders.

METHOD

We conducted a bidirectional two-sample Mendelian randomisation on genome-wide association study summary data, to investigate causality between frailty and nine mental disorders. Causal effects were primarily estimated using inverse variance weighted method. Several secondary analyses were applied to verify the results. Cochran's Q-test and Mendelian randomisation Egger intercept were applied to evaluate heterogeneity and pleiotropy.

RESULTS

Genetically determined frailty was significantly associated with increased risk of major depressive disorder (MDD) (odds ratio 1.86, 95% CI 1.36-2.53, P = 8.1 × 10-5), anxiety (odds ratio 2.76, 95% CI 1.56-4.90, P = 5.0 × 10-4), post-traumatic stress disorder (PTSD) (odds ratio 2.56, 95% CI 1.69-3.87, P = 9.9 × 10-6), neuroticism (β = 0.25, 95% CI 0.11-0.38, P = 3.3 × 10-4) and insomnia (β = 0.50, 95% CI 0.25-0.75, P = 1.1 × 10-4). Conversely, genetic liability to MDD, neuroticism, insomnia and suicide attempt significantly increased risk of frailty (MDD: β = 0.071, 95% CI 0.033-0.110, P = 2.8 × 10-4; neuroticism: β = 0.269, 95% CI 0.173-0.365, P = 3.4 × 10-8; insomnia: β = 0.160, 95% CI 0.141-0.179, P = 3.2 × 10-61; suicide attempt: β = 0.056, 95% CI 0.029-0.084, P = 3.4 × 10-5). There was a suggestive detrimental association of frailty on suicide attempt and an inverse relationship of subjective well-being on frailty.

CONCLUSIONS

Our findings show bidirectional causal associations between frailty and MDD, insomnia and neuroticism. Additionally, higher frailty levels are associated with anxiety and PTSD, and suicide attempts are correlated with increased frailty. Understanding these associations is crucial for the effective management of frailty and improvement of mental disorders.

Computer reconstruction of gene networks controlling anxiety levels in humans and laboratory mice

Anxiety is a normotypic human condition, and like any other emotion has an adaptive value. But excessively high or low anxiety has negative consequences for adaptation, which primarily determines the importance of studying these two extreme conditions. At the same time, it is known that the perception of aversive stimuli associated with anxiety leads to changes in the activity of the brain's cingulate cortex. The advantage of animals as models in studying the genetic bases of anxiety in humans is in the ability to subtly control the external conditions of formation of a certain state, the availability of brain tissues, and the ability to create and study transgenic models, including through the use of differentially expressed genes of small laboratory animals from the family Muridae with low and high anxiety. Within the framework of the translational approach, a three-domain potential gene network, which is associated with generalized anxiety in humans, was reconstructed using mouse models with different levels of anxiety by automatically analyzing the texts of scientific articles. One domain is associated with reduced anxiety in humans, the second with increased anxiety, and the third is a dispatcher who activates one of the two domains depending on the status of the organism (genetic, epigenetic, physiological). Stages of work: (I) A list of genes expressed in the cingulate cortex of the wild type CD-1 mouse line from the NCBI GEO database (experiment GSE29014). Using the tools of this database, differences in gene expression levels were revealed in groups of mice with low and high (relatively normal) anxiety. (II) Search for orthologs of DEG in humans and mice associated with anxiety in the OMA Orthology database. (III) Computer reconstruction using the ANDSystem cognitive system based on (a) human orthologous genes from stage (III), (b) human genes from the MalaCards database associated with human anxiety. The proven methods of the translational approach for the reconstruction of gene networks for behavior regulation can be used to identify molecular genetic markers of human personality traits, propensity to psychopathology.

A brain DNA co-methylation network analysis of psychosis in Alzheimer's disease

INTRODUCTION

The presence of psychosis in Alzheimer's disease (AD) is suggested to be associated with distinct molecular and neuropathological profiles in the brain.

METHODS

We assessed brain DNA methylation in AD donors with psychosis (AD+P) and without psychosis (AD-P) using the EPIC array. Weighted gene correlation network analysis identified modules of co-methylated genes in a discovery cohort (PITT-ADRC: N = 113 AD+P, N = 40 AD-P), with validation in an independent cohort (BDR: N = 79 AD+P, N = 117 AD-P), with Gene Ontology and cell-type enrichment analysis. Genetic data were integrated to identify methylation quantitative trait loci (mQTLs), which were co-localized with GWAS for related traits.

RESULTS

We replicated one AD+P associated module, which was enriched for synaptic pathways and in excitatory and inhibitory neurons. mQTLs in this module co-localized with variants associated with schizophrenia and educational attainment.

DISCUSSION

This represents the largest epigenetic study of AD+P to date, identifying pleiotropic relationships between AD+P and related traits.

HIGHLIGHTS

DNA methylation was assessed in the prefrontal cortex in subjects with AD+P and AD-P. WGCNA identified six modules of co-methylated loci associated with AD+P in a discovery cohort. One of the modules was replicated in an independent cohort. This module was enriched for synaptic genes and in excitatory and inhibitory neurons. mQTLs mapping to genes in the module co-localized with GWAS loci for schizophrenia and educational attainment.

Genetic predisposition for negative affect predicts mental health burden during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic was accompanied by an increase in mental health challenges including depression, stress, loneliness, and anxiety. Common genetic variants can contribute to the risk for psychiatric disorders and may present a risk factor in times of crises. However, it is unclear to what extent polygenic risk played a role in the mental health response to the COVID-19 pandemic. In this study, we investigate whether polygenic scores (PGSs) for mental health-related traits can distinguish between four resilience-vulnerability trajectories identified during the COVID-19 pandemic and associated lockdowns in 2020/21. We used multinomial regression in a genotyped subsample (n = 1316) of the CovSocial project. The most resilient trajectory characterized by the lowest mental health burden and the highest recovery rates served as the reference group. Compared to this most resilient trajectory, a higher value on the PGS for the well-being spectrum decreased the odds for individuals to be in one of the more vulnerable trajectories (adjusted R-square = 0.3%). Conversely, a higher value on the PGS for neuroticism increased the odds for individuals to be in one of the more vulnerable trajectories (adjusted R-square = 0.2%). Latent change in mental health burden extracted from the resilience-vulnerability trajectories was not associated with any PGS. Although our findings support an influence of PGS on mental health during COVID-19, the small added explained variance suggests limited utility of such genetic markers for the identification of vulnerable individuals in the general population.

Causal Impacts of Psychiatric Disorders on Cognition and the Mediating Effect of Oxidative Stress: A Mendelian Randomization Study

Many psychiatric disorders are associated with major cognitive deficits. However, it is uncertain whether these deficits develop as a result of psychiatric disorders and what shared risk factors might mediate this relationship. Here, we utilized the Mendelian randomization (MR) analysis to investigate the complex causal relationship between nine major psychiatric disorders and three cognitive phenotypes, while also examining the potential mediating role of oxidative stress as a shared biological underpinning. Schizophrenia (SZ), major depressive disorder (MDD), and attention deficit hyperactivity disorder (ADHD) showed a decreasing effect on cognitive performance, intelligence, and education, while bipolar disorder (BPD) increased educational attainment. MR-Clust results exhibit the shared genetic basis between SZ and other psychiatric disorders in relation to cognitive function. Furthermore, when oxidative stress was considered as a potential mediating factor, the associations between SZ and the three dimensions of cognition, as well as between MDD and intelligence and ADHD and intelligence, exhibited larger effect sizes than the overall. Mediation MR analysis also supported the causal effects between psychiatric disorders and cognition via oxidative stress traits, including carotene, vitamin E, bilirubin, and uric acid. Finally, summary-based MR identified 29 potential causal associations of oxidative stress genes with both cognitive performance and psychiatric disorders. Our findings highlight the importance of considering oxidative stress in understanding and potentially treating cognitive impairments associated with psychiatric conditions.

Mental illness and antibody responses after COVID-19 vaccination in a prospective population-based study in Catalonia

Background Mental illnesses have been overlooked as a potential factor influencing antibody responses to COVID-19 vaccine. Associations between mental disorders and antibody response might vary by specific disorders, depend on the long-term course of the illness and relate to psychotropic treatment.

METHODS

The association between mental illness diagnoses (mood affective disorders, anxiety disorders, other) over ten years and psychotropic drug prescription based on electronic health records with antibody levels (IgG and IgA) post COVID-19 vaccination was assessed in 939 vaccinated adults from Catalonia, Spain. We employed linear regression models to assess associations between specific mental illnesses and psychotropic drugs with antibody levels, correcting for demographics, comorbidities and lifestyle factors. In a genotyped subset (n = 247) we assessed the effect of polygenic risk scores (PRS) for mental illnesses and performed a two-sample mendelian randomization (MR) analysis to examine causality between mental illness and antibody responses.

RESULTS

Mood affective disorders were associated with lower IgG to receptor binding domain (RBD) [percentage change = -26.37 (95 % CI, -42.00, -6.54)]. Diagnosis of anxiety disorders was not associated with the outcome. The group of other diagnoses (mainly including insomnia and nicotine dependence) were associated with lower IgG RBD levels [percentage change: -21.53 (95 % CI, -35.38, -4.71)] and recent onset cases (≤5 years ago) showed greater decline in antibody levels. Participants on second-generation antipsychotics and multiple classes of psychotropic drugs in the last 6 months exhibited lower antibody levels. In the genotyped population, higher genetic liability (higher PRS) to schizophrenia was associated with lower IgG RBD levels [percentage change = -35.49 (95 % CI, -56.55, -4.23)]. MR analysis revealed a causal relationship between major depression genetic instrumental variables and lower IgG RBD and S levels.

CONCLUSIONS

These findings raise concerns about the efficacy of COVID-19 vaccines and potentially of other vaccines as well, in individuals with mood affective disorders, current/recent insomnia and nicotine dependence and people on multiple psychotropic drugs. Whether these associations are translated into increased risk for breakthrough infections and immune mediated long-term sequels of the SARS-CoV-2 infection warrants further investigation.

Causal associations between iron levels in subcortical brain regions and psychiatric disorders: a Mendelian randomization study

Despite observational studies linking brain iron levels to psychiatric disorders, the exact causal relationship remains poorly understood. This study aims to examine the relationship between iron levels in specific subcortical brain regions and the risk of psychiatric disorders. Utilizing two-sample Mendelian randomization (MR) analysis, this study investigates the causal associations between iron level changes in 16 subcortical nuclei and eight major psychiatric disorders, including schizophrenia (SCZ), major depressive disorder (MDD), autism spectrum disorders (ASD), attention-deficit/hyperactivity disorder, bipolar disorder, anxiety disorders, obsessive-compulsive disorder, and insomnia. The genetic instrumental variables linked to iron levels and psychiatric disorders were derived from the genome-wide association studies data of the UK Biobank Brain Imaging and Psychiatric Genomics Consortium. Bidirectional causal estimation was primarily obtained using the inverse variance weighting (IVW) method. Iron levels in the left substantia nigra showed a negative association with the risk of MDD (ORIVW = 0.94, 95% CI = 0.91-0.97, p < 0.001) and trends with risk of SCZ (ORIVW = 0.90, 95% CI = 0.82-0.98, p = 0.020). Conversely, iron levels in the left putamen were positively associated with the risk of ASD (ORIVW = 1.11, 95% CI = 1.04-1.19, p = 0.002). Additionally, several bidirectional trends were observed between subcortical iron levels and the risk for psychiatric disorders. Lower iron levels in the left substantia nigra may increase the risk of MDD, and potentially increase the risk of SCZ, indicating a potential shared pathogenic mechanism. Higher iron levels in the left putamen may lead to the development of ASD. The observed bidirectional trends between subcortical iron levels and psychiatric disorders, indicate the importance of the underlying biomechanical interactions between brain iron regulation and these disorders.

Association of childhood maltreatment and adverse lifetime experiences with post-injury psychopathology: evidence from the China Severe Trauma Cohort

BACKGROUND

Adverse life experiences have been associated with increased susceptibilities to psychopathology in later life. However, their impact on psychological responses following physical trauma remains largely unexplored.

METHODS

Based on the China Severe Trauma Cohort, we conducted a cohort study of 2937 patients who were admitted to the Trauma Medical Center of West China Hospital between June 2020 and August 2023. Adverse life experiences, including childhood maltreatment (5 subtypes, measured by Childhood Trauma Questionnaire-Short Form) and adverse lifetime experiences (17 subtypes, by Life Events Checklist) were assessed. Generalized linear mixed models were used to examine the associations of childhood maltreatment and adverse lifetime experiences with symptoms of psychopathology measured at multiple time-points after the index injury (i.e., at recruitment, 1-, 3-, 6-, and 12-month follow-ups), adjusted for important confounders. We further stratified the analyses by level of genetic predisposition to a given psychological symptom quantified by polygenic risk score (PRS) based on publicly available GWAS summary statistics. Mediation analyses were performed to assess the role of adverse lifetime experiences in connecting childhood maltreatment and post-injury psychopathology.

RESULTS

The mean age of participants was 47.95 years with a predominance of males (61.39%). During the whole follow-up period, the incidence of symptoms of stress-related disorders, anxiety, and depression was 13.86%, 29.89%, and 36.57%, respectively. We observed associations between the cumulative number of those studied adversities and increased risk of post-injury psychopathology, particularly stress-related disorder (odds ratio [OR] = 2.78, 95% confidence interval [CI] 1.87-4.12 for ≥ 2 vs no childhood maltreatment; 2.65 [1.67-4.20] for ≥ 4 vs 0-1 adverse lifetime experiences). By subtype, positive associations were observed for most studied life adversities, with the most pronounced estimates for childhood emotional abuse (ORs = 1.71-2.52) and lifetime life-threatening illness/injury (ORs = 1.87-2.89). We found basically comparable estimates among traumatized individuals with different PRSs for studied psychopathology. Moreover, adverse lifetime experiences may partially (mediation proportion: 22.52-27.48%) explain the associations between various childhood maltreatment and post-injury psychopathology.

CONCLUSIONS

Both childhood maltreatment and adverse lifetime experiences were associated with post-injury psychopathology, irrespective of genetic susceptibility. Such findings highlight the importance of close surveillance and timely psychological interventions for injury patients with adverse life experiences.

Exploring the genetic landscape of the brain-heart axis: A comprehensive analysis of pleiotropic effects between heart disease and psychiatric disorders

BACKGROUND

The genetic links between heart disease and psychiatric disorders are complex and not well understood. This study uses genome-wide association studies (GWAS) and advanced multilevel analyses to explore these connections.

METHODS

We analyzed GWAS data from seven psychiatric disorders and five types of heart disease. Genetic correlations and overlaps were examined using linkage disequilibrium score regression (LDSC), high-definition likelihood (HDL), and Genetic analysis incorporating Pleiotropy and Annotation (GPA). Pleiotropic single-nucleotide variations (SNVs) were identified with pleiotropic analysis under the composite null hypothesis (PLACO) and annotated via Functional mapping and annotation of genetic associations (FUMA). Potential pleiotropic genes were identified using Multi-marker Analysis of GenoMic Annotation (MAGMA) and Summary data-based Mendelian Randomization (SMR).

RESULTS

Among 35 trait pairs, 32 showed significant genetic correlations or overlaps. PLACO identified 15,077 SNVs, with 287 recognized as pleiotropic loci and 20 colocalization sites. MAGMA and SMR revealed 75 potential pleiotropic genes involved in diverse pathways, including cancer, neurodevelopment, and cellular organization. Mouse Genome Informatics (MGI) queries provided evidence linking multiple genes to heart or psychiatric disorders.

CONCLUSIONS

This analysis reveals loci and genes with pleiotropic effects between heart disease and psychiatric disorders, highlighting shared biological pathways. These findings illuminate the genetic mechanisms underlying the brain-heart axis and suggest shared biological foundations for these conditions, offering potential targets for future prevention and treatment strategies.

Modifiable factors for irritable bowel syndrome: evidence from Mendelian randomisation approach

ABSTRACT

Background

The potential modifiable factors influencing irritable bowel syndrome (IBS) have not been thoroughly documented. We aimed to systematically investigate the modifiable factors associated with IBS, while accounting for the impact of unobserved confounders and coexisting disorders.

Methods

Genetic correlation and Mendelian randomisation (MR) analyses were integrated to identify potential modifiable factors and coexisting disorders linked to IBS. Subsequently, multiresponse MR (MR2) was employed to further examine these associations. Summary-level genome-wide association data were used. Modifiable factors and coexisting disorders (ie, gastrointestinal and psychiatric disorders) were identified based on evidence from cohort studies and meta-analysis. In all analyses, IBS was the primary outcome, while in the MR2 analysis, coexisting disorders were also treated as outcomes alongside IBS.

Results

Most identified modifiable factors and coexisting disorders exhibited genetic correlations with IBS. MR analyses revealed strong causation between IBS and multisite chronic pain (OR=2.20, 95% CI 1.82 to 2.66), gastro-oesophageal reflux disease (OR=1.31, 95% CI 1.23 to 1.39), well-being spectrum (OR=0.17, 95% CI 0.13 to 0.21), life satisfaction (OR=0.31, 95% CI 0.25 to 0.38), positive affect (OR=0.30, 95% CI 0.24 to 0.37), neuroticism score (OR=1.20, 95% CI 1.16 to 1.25) and depression (OR=1.50, 95% CI 1.37 to 1.66). Additionally, smoking, alcohol frequency, college or university degree, intelligence, childhood maltreatment, frailty index, diverticular disease of the intestine and schizophrenia were suggestively associated with IBS. Robust associations were found between multisite chronic pain and both IBS and coexisting disorders.

Conclusions

Our study identified a comprehensive array of potential modifiable factors and coexisting disorders associated with IBS, supported by genetic evidence, including genetic correlation and multiple MR analyses. The presence of multisite chronic pain may offer a promising avenue for the concurrent prevention of IBS and its coexisting disorders.

Causal association between mitochondrial function and psychiatric disorders: Insights from a bidirectional two-sample Mendelian randomization study

BACKGROUND

Previous observational studies have suggested that there appears to be a close association between mitochondrial function and psychiatric disorders, but whether a causal role exists remains unclear.

METHODS

We extracted genetic instruments for 67 mitochondrial-related proteins and 10 psychiatric disorders from publicly available genome-wide association studies, and employed five distinct MR methods and false discovery rate correction to detect causal associations between them. Additionally, we conducted a series of sensitivity tests and additional model analysis to ensure the robustness of the results. For potential causal associations, we further performed reverse MR analyses to assess the impact of reverse causality.

RESULTS

We identified a total of 2 significant causal associations and 24 suggestive causal associations. Specifically, Phenylalanine-tRNA ligase was found to increase the risk of Alzheimer's disease, while Mitochondrial glutamate carrier 2 decreased the risk of autism spectrum disorder. Furthermore, there was no evidence of significant pleiotropy, heterogeneity, or reverse causality.

LIMITATIONS

This study was limited to individuals of European ancestry, and the conclusions drawn are merely revelatory.

CONCLUSION

This study provides novel insights into the relationship between mitochondria and psychiatric disorders, as well as the pathogenesis and treatment strategies for psychiatric disorders.

Advances in neuroscience research and big data's analysis on anxiety disorder

Anxiety disorder is a complex disease with the influence of environmental and genetic factors and multimolecular participation, and it is also one of the most common mental disorders. The causes of disorders are not clear but may include a variety of social, psychological, and biological factors. Therefore, neither genetics, neurobiology, nor neuroimaging can independently explain the pathological mechanism. By searching the Web of Science databases, Derwent Innovation Patent database, ClinicalTrials.gov database, and Cortellis database, we analyze the current situation of papers, patents, clinical trials, and drugs of anxiety disorder. Second, the existing literature was reviewed to summarize the neurophysiological mechanism, brain imaging, gene, anti-anxiety drugs, and other aspects of anxiety disorders. This article reviews the research status of anxiety disorders. The heterogeneity of the disease, lack of treatment effectiveness, and gaps in translational medicine still present barriers to further advancement. Thus, in-depth explorations of the underlying biological mechanisms of anxiety disorders, the detection and intervention of biological targets, and further developments based on existing intervention strategies will drive future research on anxiety disorders. This article is categorized under: Neuroscience > Clinical.

Association of anxiety disorder, depression, and bipolar disorder with autoimmune thyroiditis: A bidirectional two-sample mendelian randomized study

BACKGROUND

Anxiety disorder, depression, and bipolar disorder are common psychiatric disorders, and their association with autoimmune thyroiditis (AIT) has been of great interest. This study aimed to investigate the potential causal relationship between these psychiatric disorders and AIT.

METHODS

We used publicly available summary statistics from large-scale genome-wide association studies to select, quality control and cluster genetic variant loci associated with anxiety disorder, depression, bipolar disorder and AIT as instrumental variables (IVs). The Mendelian randomization (MR) study mainly used inverse variance weighting (IVW) combined with MR-egger regression and weighted median estimation (WME) to estimate bidirectional causality between mental disorders and AIT. In addition, we conducted heterogeneity and multivariate tests to verify the validity of IVW.

RESULTS

Two-sample bidirectional MR analysis revealed a positive causal link between depression and AIT. The forward MR analysis of IVW (OR 1.614, 95 % CI 1.104-2.358, P = 0.013) and WME (OR 2.314, 95 % CI 1.315-4.074, P = 0.004) demonstrated thatdepression potentially elevate the risk of AIT development, while, our investigation did not uncover a causal relationship between anxiety disorder, bipolar disorder and AIT. The results of reverse MR analysis showed that there was no significant causal relationship between AIT and anxiety disorder, depression, and bipolar disorder (P > 0.05).

CONCLUSIONS

The results of the forward MR analysis suggest a positive association between depression, and AIT risk, while indicating no support for a causal link between anxiety disorder or bipolar disorder and AIT risk based on the current data. Subsequent studies will be essential for elucidating the biological mechanisms and potential confounders underlying these associations.

Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus

BACKGROUND

Increasing evidence suggests a complex interplay between psychiatric disorders and metabolic dysregulations. However, most research has been limited to specific disorder pairs, leaving a significant gap in our understanding of the broader psycho-metabolic nexus.

METHODS

This study leveraged large-scale cohort data and genome-wide association study (GWAS) summary statistics, covering 8 common psychiatric disorders and 43 metabolic traits. We introduced a comprehensive analytical strategy to identify shared genetic bases sequentially, from key genetic correlation regions to local pleiotropy and pleiotropic genes. Finally, we developed polygenic risk score (PRS) models to translate these findings into clinical applications.

FINDINGS

We identified significant bidirectional clinical risks between psychiatric disorders and metabolic dysregulations among 310,848 participants from the UK Biobank. Genetic correlation analysis confirmed 104 robust trait pairs, revealing 1088 key genomic regions, including critical hotspots such as chr3: 47588462-50387742. Cross-trait meta-analysis uncovered 388 pleiotropic single nucleotide variants (SNVs) and 126 shared causal variants. Among variants, 45 novel SNVs were associated with psychiatric disorders and 75 novel SNVs were associated with metabolic traits, shedding light on new targets to unravel the mechanism of comorbidity. Notably, RBM6, a gene involved in alternative splicing and cellular stress response regulation, emerged as a key pleiotropic gene. When psychiatric and metabolic genetic information were integrated, PRS models demonstrated enhanced predictive power.

INTERPRETATION

The study highlights the intertwined genetic and clinical relationships between psychiatric disorders and metabolic dysregulations, emphasising the need for integrated approaches in diagnosis and treatment.

FUNDING

The National Key Research and Development Program of China (2023YFC2506200, SHH). The National Natural Science Foundation of China (82273741, SY).

Linking ambient air pollution to mental health: evidence based on the two-sample Mendelian randomization and colocalization study

Growing evidence links air pollution, a ubiquitous environmental stressor, to a higher risk of developing mental disorders, raising significant public health concerns. Mental disorders represent a significant global public health challenge which can have a profound impact on individual lives. In this study, we used Mendelian randomization (MR) to investigate the causal relationship between ambient air pollution and four common mental disorders. Genome-wide association study (GWAS) data for ambient air pollution and summary-level GWAS data for four representative mental disorders were obtained from open-access database. Inverse variance weighted (IVW) method with multiplicative random-effects model was the main analysis. Sensitivity analyses were conducted to validate the results. Bayesian colocalization analysis was conducted to explore the potential shared genetic causal variants between specific air pollutants and mental disorders. A suggestive association was observed between political matter (PM) 2.5 and anxiety disorders (OR 2.96, 95%CI 1.29-6.81, p = 0.010). Exposure to nitrogen dioxide (NO2) was significantly linked to an elevated risk of schizophrenia (OR 1.95, 95% CI 1.45-2.63, p = 1.13E-05) and showed a nominal association with an increased risk of bipolar disorder (OR 1.43, 95% CI 1.09-1.86, p = 0.009). A suggestive causal association was detected between nitrogen oxides (NOx) and anxiety disorder (OR 2.90, 95%CI 1.21-6.97, p = 0.017). No significant association was detected between exposure to PM2.5-10, PM10 and mental disorders. No significant horizonal pleiotropy and heterogeneity was found. The colocalization analysis revealed robust evidence supporting the colocalization of NO2 with schizophrenia at SNP rs12203592. Our findings support causal associations between exposure to ambient air pollution, particularly PM2.5, NO2, and NOx, and an increased risk of specific mental disorders.

The Causal Relationships Between Inflammatory Proteins, Brain Structure, and Psychiatric Disorders: A Two-Step Mendelian Randomization Analysis

BACKGROUND AND HYPOTHESIS

Inflammatory proteins are implicated in psychiatric disorders, but the causality and underlying mechanisms remain unclear.

STUDY DESIGN

We conducted bidirectional Mendelian randomization (MR) using genetic variants from genome-wide association studies (GWAS) for 91 inflammatory proteins (N = 14 824) and 11 psychiatric disorders (N = 9725 to 1 035 760). The primary analysis used the inverse variance weighted (IVW) method, with additional sensitivity analyses to confirm robustness. A two-step MR approach assessed whether brain imaging-derived phenotypes (IDPs) mediated the observed effects.

STUDY RESULTS

Forward MR analysis found the protective effect of CD40 on schizophrenia (SCZ) (IVW OR = 0.90, P = 5.29 × 10-6) and bipolar disorder (BD) (IVW OR = 0.89, P = 5.08 × 10-6). Reverse MR demonstrated that increased genetic risk of Tourette's syndrome (TS) was associated with reduced Fms-associated tyrosine kinase 3 ligand (Flt3L) levels (Flt3L) (Wald Ratio beta = -0.42, P = 1.99 × 10-7). The protective effect of CD40 on SCZ was partially mediated by the modulation of fractional anisotropy (FA) values in the right and left superior frontal occipital fasciculus, with mediation proportions of 9.6% (P = .025) and 11.5% (P = .023), respectively.

CONCLUSION

CD40 exerts an immunoprotective effect on SCZ and BD, and the effect of CD40 on SCZ was partially mediated through modulation of FA values in the superior frontal occipital fasciculus. These findings enhance comprehension of the etiology of these psychiatric conditions and underscore the promise of therapeutic strategies aimed at inflammatory proteins.

The X-linked intellectual disability gene CUL4B is critical for memory and synaptic function

Cullin 4B (CUL4B) is the scaffold protein in the CUL4B-RING E3 ubiquitin ligase (CRL4B) complex. Loss-of-function mutations in the human CUL4B gene lead to syndromic X-linked intellectual disability (XLID). Till now, the mechanism of intellectual disability caused by CUL4B mutation still needs to be elucidated. In this study, we used single-nucleus RNA sequencing (snRNA-seq) to investigate the impact of CUL4B deficiency on the transcriptional programs of diverse cell types. The results revealed that depletion of CUL4B resulted in impaired intercellular communication and elicited cell type-specific transcriptional changes relevant to synapse dysfunction. Golgi-Cox staining of brain slices and immunostaining of in vitro cultured neurons revealed remarkable synapse loss in CUL4B-deficient mice. Ultrastructural analysis via transmission electron microscopy (TEM) showed that the width of the synaptic cleft was significantly greater in CUL4B-deficient mice. Electrophysiological experiments found a decrease in the amplitude of AMPA receptor-mediated EPSCs in the hippocampal CA1 pyramidal neurons of CUL4B-deficient mice. These results indicate that depletion of CUL4B in mice results in morphological and functional abnormalities in synapses. Furthermore, behavioral tests revealed that depletion of CUL4B in the mouse nervous system results in impaired spatial learning and memory. Taken together, the findings of this study reveal the pathogenesis of neurological disorders associated with CUL4B mutations and promote the identification of therapeutic targets that can halt synaptic abnormalities and preserve memory in individuals.

Identification of novel genomic loci for anxiety symptoms and extensive genetic overlap with psychiatric disorders

AIMS

Anxiety disorders are prevalent and anxiety symptoms (ANX) co-occur with many psychiatric disorders. We aimed to identify genomic loci associated with ANX, characterize its genetic architecture, and genetic overlap with psychiatric disorders.

METHODS

We included a genome-wide association study of ANX (meta-analysis of UK Biobank and Million Veterans Program, n = 301,732), schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD), and validated the findings in the Norwegian Mother, Father, and Child Cohort (n = 95,841). We employed the bivariate causal mixture model and local analysis of covariant association to characterize the genetic architecture including overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of loci associated with anxiety and shared with psychiatric disorders.

RESULTS

Anxiety was polygenic with 12.9k genetic variants and overlapped extensively with psychiatric disorders (4.1k-11.4k variants) with predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 119 novel loci for anxiety by conditioning on the psychiatric disorders, and loci shared between anxiety and MDn = 47 , BIPn = 33 , SCZn = 71 , ADHDn = 20 , and ASDn = 5 . Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways including cell adhesion and neurofibrillary tangle compared with genes annotated to the shared loci.

CONCLUSIONS

Anxiety is highly polygenic phenotype with extensive genetic overlap with psychiatric disorders, and we identified novel loci for anxiety implicating new molecular pathways. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified molecular underpinnings may lead to potential drug targets.

Lactobacillaceae-mediated eye-brain-gut axis regulates high myopia-related anxiety: from the perspective of predictive, preventive, and personalized medicine

Background

High myopia has become a major cause of blindness worldwide and can contribute to emotional deficits through its impact on the central nervous system. The potential crosstalk with gut microbiome positions high myopia as a valuable model for studying the eye-brain-gut axis, highlighting the intricate interplay between visual health, neurological function, and the gut microbiome. Understanding these connections is crucial from a predictive, preventive, and personalized medicine (PPPM) perspective, as it may reveal novel intervention targets for managing both visual and mental health.

Working hypothesis and methodology

In our study, we hypothesized that visual stimuli associated with high myopia may lead to gut microecological dysregulation, potentially triggering mood disorders such as anxiety and depression. To test this hypothesis, we assessed genetic associations between high myopia (N = 50,372) and depression (N = 674,452) as well as anxiety (N = 21,761) using inverse variance weighted as the primary analytical method. We also investigated the potential mediating role of the gut microbiome (N = 18,340). The findings were validated in an independent cohort and summarized through meta-analysis.

Results

A genetic causal relationship between high myopia and anxiety was found (odds ratio [OR] = 8.76; 95% confidence interval [CI], 2.69-28.54; p = 3.16 × 10-4), with 20.3% of the effect mediated by the gut microbiome family Lactobacillaceae (β = 0.517; 95% CI, 0.104-1.090; p = 0.037). The analysis also showed a suggestive causal relationship between high myopia and depression (OR = 1.25; 95% CI, 1.00-1.57; p = 0.048).

Conclusions

Our study shows that high myopia causes anxiety via the Lactobacillaceae family of the gut microbiome, supporting the eye-brain-gut axis concept. This underscores the need to shift from reactive to predictive, preventive, and personalized medicine (PPPM). Targeting Lactobacillaceae offers novel insights for early intervention and personalized treatment of high myopia-related anxiety and sheds light on interventions for other vision-related brain disorders.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00387-z.

DNA methylation as a possible mechanism linking childhood adversity and health: results from a 2-sample mendelian randomization study

Childhood adversity is an important risk factor for adverse health across the life course. Epigenetic modifications, such as DNA methylation (DNAm), are a hypothesized mechanism linking adversity to disease susceptibility. Yet, few studies have determined whether adversity-related DNAm alterations are causally related to future health outcomes or if their developmental timing plays a role in these relationships. Here, we used 2-sample mendelian randomization to obtain stronger causal inferences about the association between adversity-associated DNAm loci across development (ie, birth, childhood, adolescence, and young adulthood) and 24 mental, physical, and behavioral health outcomes. We identified particularly strong associations between adversity-associated DNAm and attention-deficit/hyperactivity disorder, depression, obsessive-compulsive disorder, suicide attempts, asthma, coronary artery disease, and chronic kidney disease. More of these associations were identified for birth and childhood DNAm, whereas adolescent and young adulthood DNAm were more closely linked to mental health. Childhood DNAm loci also had primarily risk-suppressing relationships with health outcomes, suggesting that DNAm might reflect compensatory or buffering mechanisms against childhood adversity rather than acting solely as an indicator of disease risk. Together, our results suggest adversity-related DNAm alterations are linked to both physical and mental health outcomes, with particularly strong impacts of DNAm differences emerging earlier in development.

Positive and negative affect, related mental health traits, and cognitive performance: shared genetic architecture and potential causality

Altered affect and cognitive dysfunction are transdiagnostic, burdensome, and pervasive features of many psychiatric conditions which remain poorly understood and have few efficacious treatments. Research on the genetic architecture of these phenotypes and causal relationships between them may provide insight into their aetiology and comorbidity. Using data from the Lifelines Cohort Study, we conducted genome-wide association studies (GWAS) on positive and negative affect and four cognitive domains (working memory, reaction time, visual learning and memory, executive function). Using publicly available large GWAS on related - albeit distinct-phenotypes (depression, anxiety, wellbeing, general cognitive ability [GCA]) we conducted genetic correlation and Mendelian randomization (MR) analyses to examine genetic overlap and causal relationships. We identified one genome-wide hit (p<5×10-8) for reaction time, and many loci with suggestive associations (p<5×10-6; N range= 11-20 independent hits) for other phenotypes. For most phenotypes, gene mapping and tissue expression analysis of suggestive hits from the GWAS showed increased gene expression in brain tissue compared to other tissues. As predicted, negative affect is genetically correlated with mental health phenotypes (depression r g=0.51; anxiety r g=0.70; wellbeing r g = -0.71) and cognitive domains are genetically correlated with GCA and brain volume (r g ≤ 0.66). Genetic correlations between negative and positive affect suggest that they are dissociable constructs (r g = -0.18) with negative affect having higher genetic overlap with GCA than positive affect (r g =-0.19 vs -0.06). This could indicate that negative affect has a higher shared neural basis with GCA than positive affect and/or GCA and negative affect may exhibit causal relationships. MR analyses suggest potential causal effects of higher GCA on reduced negative affect, reduced risk of depression and anxiety, and higher wellbeing, but little impact on positive affect. We also report evidence for potential causal effects of depression and lower wellbeing on reduced GCA. Taken together, these results suggests that GCA may be a valid target for negative affect (but not positive affect) and depression and wellbeing may be valid targets for GCA.

The Influence of Genetic and Environmental Factors on Anxiety among Chinese Adolescents: A Twin Study

This study explored the influence of genetic and environmental factors on adolescent anxiety. Ninety-eight monozygotic and dizygotic twins from Chongqing, China (aged 15-18 years) were assessed for anxiety with the Self-Rating Anxiety Scale (SAS). The Parenting Styles and Dimensions Questionnaire (PSDQ) and Strengths and Difficulties Questionnaire (SDQ) were applied to assess environmental factors. Venous blood was drawn from the twins for zygosity determination. Structural equation modeling was performed to evaluate the effects of additive genetic factors (A), common environmental factors (C), and individual-specific environmental factors (E) on adolescent anxiety. The estimates of A and E on adolescent anxiety were 0.34 (95% CI = 0.12-0.53) and 0.66 (95% CI:0.47-0.89), respectively. The environment played an important role in adolescent anxiety. Adolescent anxiety was significantly positively correlated with peer relations (r = 0.606, p < 0.05) and negatively correlated with prosocial behavior (r = 0.207, p < 0. 05). No sex differences were observed. Adolescent anxiety was influenced by both genetic and environmental factors. The individual-specific environmental factors played an important role. Consideration of these variables will facilitate the targeted and individualized implementation of specific interventions for adolescent anxiety.

Exploring the intersection of polygenic risk scores and prenatal alcohol exposure: Unraveling the mental health equation

BACKGROUND

Prenatal alcohol exposure poses significant risks to offspring mental health. However, the interplay between genetic predispositions to mental health disorders and prenatal alcohol exposure remains incompletely understood, limiting our ability to develop effective interventions for these conditions.

METHODS

Data from the Adolescent Brain and Cognitive Development (ABCD) Study were analyzed to explore associations between polygenic risk scores (PRS) for mental disorders and maternal alcohol consumption during pregnancy. Logistic regression and structural equation modeling were utilized to assess these relationships.

RESULTS

Maternal alcohol consumption after pregnancy awareness was significantly associated with an increased genetic risk for specific mental health disorders, particularly bipolar disorder in offspring. The relationship between maternal alcohol consumption and mental health outcomes was influenced by polygenic risk scores, with both externalizing and internalizing problems being affected.

CONCLUSIONS

Our findings highlight the specific interaction between increased genetic risk for bipolar disorder and prenatal alcohol exposure in shaping offspring mental health outcomes. The significant associations we observed underscore the importance of considering both polygenic risk scores and prenatal alcohol exposure when assessing mental health risks in children. These insights emphasize the need for targeted interventions that address both genetic predispositions and environmental exposures to better understand and mitigate the impact on offspring mental health.