Brainwide Mendelian Randomization Study of Anxiety Disorders and Symptoms

Integration of Metabolomic and Brain Imaging Data Highlights Pleiotropy Among Posttraumatic Stress Disorder, Glycoprotein Acetyls, and Pallidum Structure

Background

The development of posttraumatic stress disorder (PTSD) is attributable to the interplay between exposure to severe traumatic events, environmental factors, and biological characteristics. Blood and brain imaging markers have been associated with PTSD. However, to our knowledge, no study has systematically investigated the genetic relationship between PTSD, metabolic biomarkers, and brainwide imaging.

Methods

We integrated genome-wide data informative of PTSD, 233 metabolic biomarkers, and 3935 brain imaging-derived phenotypes (IDPs). Pleiotropy was assessed by applying global and local genetic correlation, colocalization, and genetically inferred causality.

Results

We observed significant genetic overlap between PTSD and glycoprotein acetyls (GlycA) (a stable inflammatory biomarker) in 2 independent cohorts (discovery r g = 0.26, p = 1.00 × 10-4; replication r g = 0.23, p = 5.99 × 10-19). Interestingly, there was no genetic correlation between anxiety and GlycA (p = .33). PTSD and GlycA were both genetically correlated with median T2∗ in the left pallidum (IDP-1444: r g = 0.14, p = 1.39 × 10-5; r g = -0.38, p = 2.50 × 10-3, respectively). Local genetic correlation between PTSD and GlycA was observed in 7 genetic regions (p < 2.0 × 10-5), mapping genes related to immune and stress response, inflammation, and metabolic processes. Furthermore, we identified 1 variant, rs12048743, with evidence of horizontal pleiotropy linking GlycA and IDP-1444 (z IDP-1444 = 17.14, z GlycA = -6.07, theta p = 2.06 × 10-8). Regional colocalization was observed among GlycA, IDP-1444, and tissue-specific transcriptomic regulation for brain frontal cortex and testis (rs12048743-chr1q32.1; posterior probability > 0.8). While we also tested causality between PTSD, metabolomic biomarkers, and brain IDPs, these were not consistent across different genetically informed causal inference methods.

Conclusions

Our findings highlight a new putative pleiotropic mechanism that links systemic inflammation and pallidum structure to PTSD.

Causal relationships between white matter connectome and mental disorders: a large-scale genetic correlation study

BACKGROUND

Abnormalities in white matter integrity in mental disorders have attracted widespread attention, yet the genetic correlations and causal effects between white matter structural connectome and various psychiatric conditions remain largely unexplored.

METHODS

In this study, we employed linkage disequilibrium score (LDSC) and high-definition likelihood (HDL) methods to analyze genetic correlations between white matter connectome and mental disorders, followed by bidirectional two-sample Mendelian randomization (MR) analysis to investigate causal relationships. We utilized 206 white matter connectome magnetic resonance imaging (MRI) phenotypes derived from the processed UK Biobank dataset (n = 26,333 individuals) and 12 mental disorders from the latest FinnGen database (n = 402,965 to 449,029 individuals).

RESULTS

Using both methods, we observed 26 pairs of brain white matter connectivity phenotypes and mental disorders showing significant correlations. Forward MR analysis identified two white matter structural connectome phenotypes causally associated with psychiatric disorder risk. Increased connectivity in left-hemisphere visual network(VIS) to right-hemisphere limbic network(LIM)white-matter structural connectivity was associated with increased risk of anxiety disorders. Additionally, decreased connectivity in left-hemisphere visual network to hippocampus white-matter structural connectivity was associated with reduced risk of post-traumatic stress disorder (PTSD). However, reverse MR analysis results did not survive multiple testing correction.

CONCLUSION

These findings provide crucial insights into the complex interplay between white matter structural connectivity and mental disorders, potentially offering new avenues for understanding the neurobiological underpinnings of psychiatric conditions and informing future diagnostic and therapeutic strategies.

Prevalence and network structure of depression, anxiety and adverse doctor-patient relationship risks among patients with physical diseases: A cross-sectional study

BACKGROUND

Mental health issues among patients with physical diseases are increasingly common. This study investigated the prevalence of depression, anxiety, and adverse doctor-patient relationship risks (ADRR) among patients with physical diseases, and the central and bridge symptoms of this network structure.

METHODS

A total of 14,344 patients with physical diseases enrolled in this survey. The Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Psychological Safety Questionnaire were used to evaluate anxiety, depression, and ADRR. The "qgraph" package in R 4.4.3 was used to construct a network model to identify central and bridge symptoms.

RESULTS

The prevalence rates of depression, anxiety, and ADRR were found to be 9.52 % (95 % confidence interval (CI): 9.04-10.00 %), 19.35 % (95 % CI: 18.71-20.00 %), and 4.29 % (95 % CI: 3.96-4.62 %), respectively. Within the network structure, the central symptoms identified were 'Sad mood,' 'Restlessness,' and 'Excessive worry,' which also served as the bridge symptoms. The flow network analysis revealed that ADRR exhibited the strongest associations with 'Anhedonia', 'Restlessness', and 'Suicidal ideation'. Additionally, 'Suicidal ideation' shows strongest correlations with 'Guilt', 'Concentration', and 'Restlessness'.

LIMITATION

The generalizability of the study's findings is constrained, as the sample consisted exclusively of inpatients, potentially limiting applicability to non-hospitalized individuals with physical illnesses.

CONCLUSION

This study provides novel insights into the comorbidity of depression, anxiety, and ADRR at the symptom level in patients with physical diseases through the application of network analysis. The identification of bridge symptoms highlights potential targets for interventions aimed at addressing the comorbidity among these disorders.

Temporomandibular disorders and mental health: shared etiologies and treatment approaches

The biopsychosocial model suggests that temporomandibular disorders (TMDs) often coexist with mental health disorders, particularly depression and anxiety, affecting a significant portion of the global population. The interplay between TMDs and mental health disorders contributes to a complex comorbidity, perpetuating a cycle of mutual influence and reinforcement. This review investigates the neurobiological mechanisms and epidemiological evidence supporting the shared etiology of TMDs and mental health disorders, exploring potential shared vulnerabilities and bidirectional causal relationships. Shared vulnerabilities between TMDs and mental health disorders may stem from genetic and epigenetic predispositions, psychosocial factors, and behavioral aspects. Inflammatory cytokines, neurotransmitters, neurotrophins, and neuropeptides play pivotal roles in both peripheral and central sensitization as well as neuroinflammation. Brain imaging studies suggest that TMDs and mental health disorders exhibit overlapping brain regions indicative of reward processing deficits and anomalies within the triple network model. Future research efforts are crucial for developing a comprehensive understanding of the underlying mechanisms and confirming the reciprocal causal effects between TMDs and mental health disorders. This review provides valuable insights for oral healthcare professionals, stressing the importance of optimizing treatment strategies for individuals dealing with concurrent TMDs and mental health issues through a personalized, holistic, and multidisciplinary approach.

Brain-wide pleiotropy investigation of alcohol drinking and tobacco smoking behaviors

To investigate the pleiotropic mechanisms linking brain structure and function to alcohol drinking and tobacco smoking, we integrated genome-wide data generated by the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN; up to 805,431 participants) with information related to 3935 brain imaging-derived phenotypes (IDPs) available from UK Biobank (N = 33,224). We observed global genetic correlation of smoking behaviors with white matter hyperintensities, the morphology of the superior longitudinal fasciculus, and the mean thickness of pole-occipital. With respect to the latter brain IDP, we identified a local genetic correlation with age at which the individual began smoking regularly (hg38 chr2:35,895,678-36,640,246: rho = 1, p = 1.01 × 10-5). This region has been previously associated with smoking initiation, educational attainment, chronotype, and cortical thickness. Our genetically informed causal inference analysis using both latent causal variable approach and Mendelian randomization linked the activity of prefrontal and premotor cortex and that of superior and inferior precentral sulci, and cingulate sulci to the number of alcoholic drinks per week (genetic causality proportion, gcp = 0.38, p = 8.9 × 10-4, rho = -0.18 ± 0.07; inverse variance weighting, IVW beta = -0.04, 95%CI = -0.07--0.01). This relationship could be related to the role of these brain regions in the modulation of reward-seeking motivation and the processing of social cues. Overall, our brain-wide investigation highlighted that different pleiotropic mechanisms likely contribute to the relationship of brain structure and function with alcohol drinking and tobacco smoking, suggesting decision-making activities and chemosensory processing as modulators of propensity towards alcohol and tobacco consumption.

War Anxiety: A Review

PURPOSE OF REVIEW

This review critically evaluates literature on war-induced anxiety, highlighting findings from 2021 to 2024, especially during the Russia-Ukraine war.

RECENT FINDINGS

Measures and prevalence estimates of anxiety and fear are updated. Populations affected by armed conflicts include residents of conflict zones and neighboring countries, internally displaced persons, refugees, combatants, and healthcare and humanitarian aid workers. Socioeconomic factors predict anxiety incidence and individuals differ in coping strategies. Anxiety could have long-term adverse effects over the life-course and across generations. Community and online interventions may reduce anxiety. The review underscores research directions in war-related anxiety's definition and assessment, risk and protective factors, health and societal consequences, and prevention and treatment approaches. The review provides an update for mental health researchers and practitioners working with the victims of war and other crises, often compounded by additional layers of stress of social inequalities, political divisions, and ethnic and racial tensions.

Obstructive sleep apnea and structural and functional brain alterations: a brain-wide investigation from clinical association to genetic causality

BACKGROUND

Obstructive sleep apnea (OSA) is linked to brain alterations, but the specific regions affected and the causal associations between these changes remain unclear.

METHODS

We studied 20 pairs of age-, sex-, BMI-, and education- matched OSA patients and healthy controls using multimodal magnetic resonance imaging (MRI) from August 2019 to February 2020. Additionally, large-scale Mendelian randomization analyses were performed using genome-wide association study (GWAS) data on OSA and 3935 brain imaging-derived phenotypes (IDPs), assessed in up to 33,224 individuals between December 2023 and March 2024, to explore potential genetic causality between OSA and alterations in whole brain structure and function.

RESULTS

In the cohort study, OSA patients exhibited significantly lower fractional amplitude of low-frequency fluctuation and regional homogeneity in the right posterior cerebellar lobe and bilateral superior and middle frontal gyrus, while showing higher levels in the left occipital lobe and left posterior central gyrus. Decreased fractional anisotropy (FA) but increased apparent diffusion coefficient (ADC) was shown in the bilateral superior longitudinal fasciculus. According to the results of Affiliation file 2: table s6, it is the ADC value of right superior longitudinal fasciculus was shown a positive correlation with the lowest oxygen saturation. In the Mendelian randomization analyses, the area of left inferior temporal sulcus (OR: 0.89; 95% CI: 0.82-0.96), rfMRI connectivity ICA100 edge 893 (OR: 0.88; 95% CI: 0.82-0.96), ICA100 edge 951 (OR: 0.89; 95% CI: 0.82-0.97), and ICA100 edge 1213 (OR: 0.89; 95% CI: 0.82-0.96) were significantly decreased in OSA. Conversely, mean thickness of G-front-inf-Triangul in right hemisphere (OR: 1.14; 95% CI: 1.05-1.23), mean orientation dispersion index in right tapetum (OR: 1.13; 95% CI: 1.04-1.23), and rfMRI connectivity ICA100 edge 258 (OR: 1.13; 95% CI: 1.04-1.22) showed opposite results.

CONCLUSIONS

Nerve fiber damage and imbalances in neuronal activity across multiple brain regions caused by hypoxia, particularly the frontal lobe, underlie the structural and the functional connectivity impairments in OSA.

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.

Causal relationships between cortical brain structural alterations and migraine subtypes: a bidirectional Mendelian randomization study of 2,347 neuroimaging phenotypes

BACKGROUND

Previous studies have shown that migraines are associated with brain structural changes. However, the causal relationships between these changes and migraine, as well as its subtypes, migraine with aura (MA) and migraine without aura (MO), remain largely unclear.

METHODS

We utilized genome-wide association study (GWAS) summary statistics from European cohorts for 2,347 cortical structural magnetic resonance imaging (MRI) phenotypes, derived from both T1-weighted and diffusion tensor imaging scans (n = 36,663), with migraine and its subtypes (n = 147,970-375,752). Cortical phenotypes included both macrostructural (e.g., cortical thickness, surface area) and microstructural (e.g., fractional anisotropy, mean diffusivity) features. Genetic correlations were first assessed to identify significant associations, followed by bidirectional Mendelian randomization (MR) analyses to determine causal relationships between these brain phenotypes and migraine, as well as its subtypes (MA and MO). Sensitivity analyses were applied to ensure the robustness of the results.

RESULTS

Genetic correlation analysis identified 510 significant associations between cortical structural phenotypes and migraine across 401 distinct traits. Forward MR analysis revealed nine significant causal effects of cortical structural changes on migraine risk. Specifically, increased cortical thickness and local gyrification index in specific cortical regions were associated with a decreased risk of overall migraine, MA, and MO, while intracellular volume fraction and orientation diffusion index in specific regions increased the risk of MA and MO. Reverse MR analysis demonstrated that MA causally increased mean diffusivity in the insular and frontal opercular cortex. Sensitivity analyses confirmed the robustness of these findings, with no evidence of horizontal pleiotropy or heterogeneity.

CONCLUSION

This study identifies causal relationships between cortical neuroimaging phenotypes and migraine, highlighting potential biomarkers for migraine diagnosis, treatment, and prevention.

Unraveling the causal relationships between depression and brain structural imaging phenotypes: A bidirectional Mendelian Randomization study

BACKGROUND

Previous studies have revealed structural brain abnormalities in individuals with depression, but the causal relationship between depression and brain structure remains unclear.

METHODS

A genetic correlation analysis was conducted using summary statistics from the largest genome-wide association studies for depression (N = 674,452) and 1,265 brain structural imaging-derived phenotypes (IDPs, N = 33,224). Subsequently, a bidirectional two-sample Mendelian Randomization (MR) approach was employed to explore the causal relationships between depression and the IDPs that showed genetic correlations with depression. The main MR results were obtained using the inverse variance weighted (IVW) method, and other MR methods were further employed to ensure the reliability of the findings.

RESULTS

Ninety structural IDPs were identified as being genetically correlated with depression and were included in the MR analyses. The IVW MR results indicated that reductions in the volume of several brain regions, including the bilateral subcallosal cortex, right medial orbitofrontal cortex, and right middle-posterior part of the cingulate cortex, were causally linked to an increased risk of depression. Additionally, decreases in surface area of the right middle temporal visual area, right middle temporal cortex, right inferior temporal cortex, and right middle-posterior part of the cingulate cortex were causally associated with a heightened risk of depression. Validation and sensitivity analyses supported the robustness of these findings. However, no evidence was found for a causal effect of depression on structural IDPs.

CONCLUSIONS

Our findings reveal the causal influence of specific brain structures on depression, providing evidence to consider brain structural changes in the etiology and treatment of depression.

Gene discovery and biological insights into anxiety disorders from a large-scale multi-ancestry genome-wide association study

We leveraged information from more than 1.2 million participants, including 97,383 cases, to investigate the genetics of anxiety disorders across five continental groups. Through ancestry-specific and cross-ancestry genome-wide association studies, we identified 51 anxiety-associated loci, 39 of which were novel. In addition, polygenic risk scores derived from individuals of European descent were associated with anxiety in African, admixed American and East Asian groups. The heritability of anxiety was enriched for genes expressed in the limbic system, cerebral cortex, cerebellum, metencephalon, entorhinal cortex and brain stem. Transcriptome-wide and proteome-wide analyses highlighted 115 genes associated with anxiety through brain-specific and cross-tissue regulation. Anxiety also showed global and local genetic correlations with depression, schizophrenia and bipolar disorder and widespread pleiotropy with several physical health domains. Overall, this study expands our knowledge regarding the genetic risk and pathogenesis of anxiety disorders, highlighting the importance of investigating diverse populations and integrating multi-omics information.

Causal relationship between resting-state networks and depression: a bidirectional two-sample mendelian randomization study

BACKGROUND

Cerebral resting-state networks were suggested to be strongly associated with depressive disorders. However, the causal relationship between cerebral networks and depressive disorders remains controversial. In this study, we aimed to investigate the effect of resting-state networks on depressive disorders using a bidirectional Mendelian randomization (MR) design.

METHODS

Updated summary-level genome-wide association study (GWAS) data correlated with resting-state networks were obtained from a meta-analysis of European-descent GWAS from the Complex Trait Genetics Lab. Depression-related GWAS data were obtained from the FinnGen study involving participants with European ancestry. Resting-state functional magnetic resonance imaging and multiband diffusion imaging of the brain were performed to measure functional and structural connectivity in seven well-known networks. Inverse-variance weighting was used as the primary estimate, whereas the MR-Pleiotropy RESidual Sum and Outliers (PRESSO), MR-Egger, and weighted median were used to detect heterogeneity, sensitivity, and pleiotropy.

RESULTS

In total, 20,928 functional and 20,573 structural connectivity data as well as depression-related GWAS data from 48,847 patients and 225,483 controls were analyzed. Evidence for a causal effect of the structural limbic network on depressive disorders was found in the inverse variance-weighted limbic network (odds ratio, [Formula: see text]; 95% confidence interval, [Formula: see text]; [Formula: see text]), whereas the causal effect of depressive disorders on SC LN was not found(OR=1.0025; CI,1.0005-1.0046; P=0.012). No significant associations between functional connectivity of the resting-state networks and depressive disorders were found in this MR study.

CONCLUSIONS

These results suggest that genetically determined structural connectivity of the limbic network has a causal effect on depressive disorders and may play a critical role in its neuropathology.

Association between gut microbiota and Hirschsprung disease: a bidirectional two-sample Mendelian randomization study

Background

Several studies have pointed to the critical role of gut microbiota (GM) and their metabolites in Hirschsprung disease (HSCR) pathogenesis. However, the detailed causal relationship between GM and HSCR remains unknown.

Methods

In this study, we used two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between GM and HSCR, based on the MiBioGen Consortium's genome-wide association study (GWAS) and the GWAS Catalog's HSCR data. Reverse MR analysis was performed subsequently, and the sensitivity analysis, Cochran's Q-test, MR pleiotropy residual sum, outlier (MR-PRESSO), and the MR-Egger intercept were used to analyze heterogeneity or horizontal pleiotropy. 16S rDNA sequencing and targeted mass spectrometry were developed for initial validation.

Results

In the forward MR analysis, inverse-variance weighted (IVW) estimates suggested that Eggerthella (OR: 2.66, 95%CI: 1.23-5.74, p = 0.01) was a risk factor for HSCR, while Peptococcus (OR: 0.37, 95%CI: 0.18-0.73, p = 0.004), Ruminococcus2 (OR: 0.32, 95%CI: 0.11-0.91, p = 0.03), Clostridiaceae1 (OR: 0.22, 95%CI: 0.06-0.78, p = 0.02), Mollicutes RF9 (OR: 0.27, 95%CI: 0.09-0.8, p = 0.02), Ruminococcaceae (OR: 0.16, 95%CI: 0.04-0.66, p = 0.01), and Paraprevotella (OR: 0.45, 95%CI: 0.21-0.98, p = 0.04) were protective factors for HSCR, which had no heterogeneity or horizontal pleiotropy. However, reverse MR analysis showed that HSCR (OR: 1.02, 95%CI: 1-1.03, p = 0.049) is the risk factor for Eggerthella. Furthermore, some of the above microbiota and short-chain fatty acids (SCFAs) were altered in HSCR, showing a correlation.

Conclusion

Our analysis established the relationship between specific GM and HSCR, identifying specific bacteria as protective or risk factors. Significant microbiota and SCFAs were altered in HSCR, underlining the importance of further study and providing new insights into the pathogenesis and treatment.

Gene Discovery and Biological Insights into Anxiety Disorders from a Multi-Ancestry Genome-wide Association Study of >1.2 Million Participants

We leveraged information from more than 1.2 million participants to investigate the genetics of anxiety disorders across five continental ancestral groups. Ancestry-specific and cross-ancestry genome-wide association studies identified 51 anxiety-associated loci, 39 of which are novel. Additionally, polygenic risk scores derived from individuals of European descent were associated with anxiety in African, Admixed-American, and East Asian groups. The heritability of anxiety was enriched for genes expressed in the limbic system, the cerebral cortex, the cerebellum, the metencephalon, the entorhinal cortex, and the brain stem. Transcriptome- and proteome-wide analyses highlighted 115 genes associated with anxiety through brain-specific and cross-tissue regulation. We also observed global and local genetic correlations with depression, schizophrenia, and bipolar disorder and putative causal relationships with several physical health conditions. Overall, this study expands the knowledge regarding the genetic risk and pathogenesis of anxiety disorders, highlighting the importance of investigating diverse populations and integrating multi-omics information.