Symptom-level modelling unravels the shared genetic architecture of anxiety and depression

Assessment and ascertainment in psychiatric molecular genetics: challenges and opportunities for cross-disorder research

Psychiatric disorders are highly comorbid, heritable, and genetically correlated [1-4]. The primary objective of cross-disorder psychiatric genetics research is to identify and characterize both the shared genetic factors that contribute to convergent disease etiologies and the unique genetic factors that distinguish between disorders [4, 5]. This information can illuminate the biological mechanisms underlying comorbid presentations of psychopathology, improve nosology and prediction of illness risk and trajectories, and aid the development of more effective and targeted interventions. In this review we discuss how estimates of comorbidity and identification of shared genetic loci between disorders can be influenced by how disorders are measured (phenotypic assessment) and the inclusion or exclusion criteria in individual genetic studies (sample ascertainment). Specifically, the depth of measurement, source of diagnosis, and time frame of disease trajectory have major implications for the clinical validity of the assessed phenotypes. Further, biases introduced in the ascertainment of both cases and controls can inflate or reduce estimates of genetic correlations. The impact of these design choices may have important implications for large meta-analyses of cohorts from diverse populations that use different forms of assessment and inclusion criteria, and subsequent cross-disorder analyses thereof. We review how assessment and ascertainment affect genetic findings in both univariate and multivariate analyses and conclude with recommendations for addressing them in future research.

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.

Comorbidity alters the genetic relationship between anxiety disorders and major depression

Importance-

There is extensive comorbidity between anxiety disorders (ANX) and major depression (MD). Most studies on the genetics of ANX do not exclude comorbid cases of MD, and vice versa, therefore confounding genetic association analyses. Disorder-specific analysis of genomic data may reveal more precise biological pathways and causal relationships.

Objective-

To investigate the genetic relationship between disorder-specific ANX and MD compared to samples with comorbidity, including their causal relationship.

Design Setting and Participants-

Data from UK Biobank was used to perform genome-wide association studies (GWAS) of ANX-only and MD-only, and generate disorder-specific polygenic risk scores (PRS). The Norwegian Mother, Father, and Child Cohort (MoBa) was used to test the associations of PRS with diagnosis and symptoms. MD and ANX GWAS data including comorbidities (MD-co and ANX-co) were used as comparators. Genetic correlation was assessed using LDSC, and Mendelian randomization was employed to infer causal relationships.

Main Outcomes and Measures

GWAS of ICD-10 diagnoses of ANX, MD, or both. Genetic correlations between pairs of ANX and MD phenotypes. PRS associations with diagnoses of ANX, MD, and their comorbid states, and anxiety or depressive symptoms.

Results-

The GWAS of ANX-only (9,980 cases and 179,442 controls) and MD-only (15,301 cases and 179,038 controls) showed a lower genetic correlation (0.53) than the one between ANX-co and MD-co (0.90). ANX-only showed a causal relationship with MD-only (PFDR=1.5e-02), but not vice versa, while comorbid cases showed a significant bidirectional causal relationship (PFDR=2.9e-12, PFDR =9.3e-06). The PRS-MD-only were differentially associated with MD-only compared to ANX-only cases (β= -0.08; 95%CI: -0.11, -0.03); however, this differential association was not observed for the PRS-MD-co. A similar pattern of differential association with anxiety and depressive symptoms was observed for PRS-ANX-only, but not for PRS-MD-co.

Conclusions and Relevance-

The genetics and underlying biology of ANX and MD are more distinct when comorbid cases are excluded from analyses and reveals that ANX may be causal for MD. This confounding of genetic relationships as a result of comorbidity is likely to apply to other psychiatric disorders. Disorder-specific genetic studies may help uncover more relevant biological mechanisms and guide more targeted clinical interventions.

Genetic variants associated with longevity in long-living Indians

Genetic factors play a significant role in determining an individual's longevity. The present study was aimed at identifying genetic variants associated with longevity in Indian population. Long living individuals (LLIs), aged 85+, were compared with younger controls, aged 18-49 years, using data from GenomegaDB, a genetic database of Indians living in India. An in-house developed custom chip, having variants associated with various cancers, cardiovascular, neurological, gastro-intestinal, metabolic and auto-immune disorders, was used to generate genotype data. Logistic regression analysis with sex and top three genetic principal components as covariates resulted in 9 variants to be significantly associated with longevity at a p-value threshold of 5 × 10-4. Alleles associated with slower heart rate (rs365990, MYH6), decreased risk of osteoporosis and short body height (rs2982570, ESR1), decreased risk of schizophrenia (rs1339227, RIMS1-KCNQ5) and decreased risk of anxiety and neuroticism (rs391957, HSPA5) were found to have higher frequency in LLIs. Alleles associated with increased risk of atrial fibrillation (rs3903239, GORAB-PRRX1) and biliary disorders (rs2002042, ABCC2) were found to have lower frequency. The G allele of rs2802292 from FOXO3A gene, associated with longevity in Japanese, German and French centenarians, was also found to be significant in this population (P = 0.032). Pathway enrichment analysis revealed that the genes involved in oxidative stress, apoptosis, DNA damage repair, glucose metabolism and energy metabolism were significantly involved in affecting the longevity. Results of our study demonstrate the genetic basis of healthy aging and longevity in the population.

Mutational landscape of risk variants in comorbid depression and obesity: a next-generation sequencing approach

Major depression (MD) and obesity are complex genetic disorders that are frequently comorbid. However, the study of both diseases concurrently remains poorly addressed and therefore the underlying genetic mechanisms involved in this comorbidity remain largely unknown. Here we examine the contribution of common and rare variants to this comorbidity through a next-generation sequencing (NGS) approach. Specific genomic regions of interest in MD and obesity were sequenced in a group of 654 individuals from the PISMA-ep epidemiological study. We obtained variants across the entire frequency spectrum and assessed their association with comorbid MD and obesity, both at variant and gene levels. We identified 55 independent common variants and a burden of rare variants in 4 genes (PARK2, FGF21, HIST1H3D and RSRC1) associated with the comorbid phenotype. Follow-up analyses revealed significantly enriched gene-sets associated with biological processes and pathways involved in metabolic dysregulation, hormone signaling and cell cycle regulation. Our results suggest that, while risk variants specific to the comorbid phenotype have been identified, the genes functionally impacted by the risk variants share cell biological processes and signaling pathways with MD and obesity phenotypes separately. To the best of our knowledge, this is the first study involving a targeted sequencing approach toward the study of the comorbid MD and obesity. The framework presented here allowed a deep characterization of the genetics of the co-occurring MD and obesity, revealing insights into the mutational and functional profile that underlies this comorbidity and contributing to a better understanding of the relationship between these two disabling disorders.

Gut microbial and human genetic signatures of inflammatory bowel disease increase risk of comorbid mental disorders

The high prevalence of comorbid mental disorders (CMDs) in patients with inflammatory bowel disease (IBD) is well-documented. This study delves into the intricate CMD-IBD relationship through comprehensive analyses using human variants, gut microbiome, and anxiety/depression estimates from a cohort of 507 IBD patients and 75 controls. Notably, patients with IBD, especially those with CMD, exhibited lower diversity than controls. We identified 106 differentially abundant taxa (DATs) in IBD patients compared to controls and 21 DATs distinguishing CMD-affected from CMD-free IBD patients. Microbial IBD-risk scores, reflecting an individual's microbial burden for IBD, revealed a significant enrichment of IBD-risk signatures in CMD-affected patients compared to CMD-free patients. Additionally, there was an IBD-risk variant potentially regulating the abundance of an IBD/CMD-associated DAT, suggesting an interplay between IBD-risk variants and dysbiosis in CMD. Our investigation underscores the pivotal role of IBD-associated gut dysbiosis in predisposing IBD patients to CMD, partially through genetic variant-mediated mechanisms.

Differential microRNA expression in adolescent anxiety proneness

Biological mechanisms underlying anxiety proneness (AP), the tendency to react fearfully to stressors due to the belief that experiencing anxiety has harmful consequences, remain unclear. Epigenetic mechanisms, such as microRNAs (small, non-coding RNAs 19-20 nucleotides long), may be contributory. This study investigated AP-associated differences in microRNA expression among South African adolescents with variable exposure to childhood trauma (CT). AP was assessed using a composite score reflecting trait anxiety and anxiety sensitivity, while CT exposure was assessed with the Childhood Trauma Questionnaire. High-quality total RNA (n = 88) extracted from whole blood underwent microRNA-sequencing. Differential microRNA expression analysis was conducted with DESeq2 in R, messenger RNA target prediction analysis was performed using TargetScan and DIANA-microT, and the DIANA mirPATH tool was used for KEGG pathway analysis. The majority of participants were female (75.86%) with an average age of 15 (±1.19) years. MicroRNA expression analysis identified upregulation of hsa-miR-28-5p and downregulation of hsa-miR-502-3p and hsa-miR-500a-3p in high-AP individuals, irrespective of CT. Four KEGG pathways, each with ≥10% of their constituent genes predicted to be targets of the differentially expressed microRNAs, were identified and were enriched for genes involved in calcineurin and glutamate signalling. These findings suggest that epigenetically mediated effects on neuronal function contribute to the molecular aetiology of AP.

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.

Polygenic Scores and Networks of Psychopathology Symptoms

Importance

Studies on polygenic risk for psychiatric traits commonly use a disorder-level approach to phenotyping, implicitly considering disorders as homogeneous constructs; however, symptom heterogeneity is ubiquitous, with many possible combinations of symptoms falling under the same disorder umbrella. Focusing on individual symptoms may shed light on the role of polygenic risk in psychopathology.

Objective

To determine whether polygenic scores are associated with all symptoms of psychiatric disorders or with a subset of indicators and whether polygenic scores are associated with comorbid phenotypes via specific sets of relevant symptoms.

Design, Setting, and Participants

Data from 2 population-based cohort studies were used in this cross-sectional study. Data from children in the Avon Longitudinal Study of Parents and Children (ALSPAC) were included in the primary analysis, and data from children in the Twins Early Development Study (TEDS) were included in confirmatory analyses. Data analysis was conducted from October 2021 to January 2024. Pregnant women based in the Southwest of England due to deliver in 1991 to 1992 were recruited in ALSPAC. Twins born in 1994 to 1996 were recruited in TEDS from population-based records. Participants with available genetic data and whose mothers completed the Short Mood and Feelings Questionnaire and the Strength and Difficulties Questionnaire when children were 11 years of age were included.

Main Outcomes and Measures

Psychopathology relevant symptoms, such as hyperactivity, prosociality, depression, anxiety, and peer and conduct problems at age 11 years. Psychological networks were constructed including individual symptoms and polygenic scores for depression, anxiety, attention-deficit/hyperactivity disorder (ADHD), body mass index (BMI), and educational attainment in ALSPAC. Following a preregistered confirmatory analysis, network models were cross-validated in TEDS.

Results

Included were 5521 participants from ALSPAC (mean [SD] age, 11.8 [0.14] years; 2777 [50.3%] female) and 4625 participants from TEDS (mean [SD] age, 11.27 [0.69] years; 2460 [53.2%] female). Polygenic scores were preferentially associated with restricted subsets of core symptoms and indirectly associated with other, more distal symptoms of psychopathology (network edges ranged between r = -0.074 and r = 0.073). Psychiatric polygenic scores were associated with specific cross-disorder symptoms, and nonpsychiatric polygenic scores were associated with a variety of indicators across disorders, suggesting a potential contribution of nonpsychiatric traits to comorbidity. For example, the polygenic score for ADHD was associated with a core ADHD symptom, being easily distracted (r = 0.07), and the polygenic score for BMI was associated with symptoms across disorders, including being bullied (r = 0.053) and not thinking things out (r = 0.041).

Conclusions and Relevance

Genetic associations observed at the disorder level may hide symptom-level heterogeneity. A symptom-level approach may enable a better understanding of the role of polygenic risk in shaping psychopathology and comorbidity.

Building machine learning prediction models for well-being using predictors from the exposome and genome in a population cohort

Effective personalized well-being interventions require the ability to predict who will thrive or not, and the understanding of underlying mechanisms. Here, using longitudinal data of a large population cohort (the Netherlands Twin Register, collected 1991-2022), we aim to build machine learning prediction models for adult well-being from the exposome and genome, and identify the most predictive factors (N between 702 and 5874). The specific exposome was captured by parent and self-reports of psychosocial factors from childhood to adulthood, the genome was described by polygenic scores, and the general exposome was captured by linkage of participants' postal codes to objective, registry-based exposures. Not the genome (R 2 = -0.007 [-0.026-0.010]), but the general exposome (R 2 = 0.047 [0.015-0.076]) and especially the specific exposome (R 2 = 0.702 [0.637-0.753]) were predictive of well-being in an independent test set. Adding the genome (P = 0.334) and general exposome (P = 0.695) independently or jointly (P = 0.029) beyond the specific exposome did not improve prediction. Risk/protective factors such as optimism, personality, social support and neighborhood housing characteristics were most predictive. Our findings highlight the importance of longitudinal monitoring and promises of different data modalities for well-being prediction.

Neuroticism/Negative Emotionality Is Associated with Increased Reactivity to Uncertain Threat in the Bed Nucleus of the Stria Terminalis, Not the Amygdala

Neuroticism/negative emotionality (N/NE)-the tendency to experience anxiety, fear, and other negative emotions-is a fundamental dimension of temperament with profound consequences for health, wealth, and well-being. Elevated N/NE is associated with a panoply of adverse outcomes, from reduced socioeconomic attainment to psychiatric illness. Animal research suggests that N/NE reflects heightened reactivity to uncertain threat in the bed nucleus of the stria terminalis (BST) and central nucleus of the amygdala (Ce), but the relevance of these discoveries to humans has remained unclear. Here we used a novel combination of psychometric, psychophysiological, and neuroimaging approaches to test this hypothesis in an ethnoracially diverse, sex-balanced sample of 220 emerging adults selectively recruited to encompass a broad spectrum of N/NE. Cross-validated robust-regression analyses demonstrated that N/NE is preferentially associated with heightened BST activation during the uncertain anticipation of a genuinely distressing threat (aversive multimodal stimulation), whereas N/NE was unrelated to BST activation during certain-threat anticipation, Ce activation during either type of threat anticipation, or BST/Ce reactivity to threat-related faces. It is often assumed that different threat paradigms are interchangeable assays of individual differences in brain function, yet this has rarely been tested. Our results revealed negligible associations between BST/Ce reactivity to the anticipation of threat and the presentation of threat-related faces, indicating that the two tasks are nonfungible. These observations provide a framework for conceptualizing emotional traits and disorders; for guiding the design and interpretation of biobank and other neuroimaging studies of psychiatric risk, disease, and treatment; and for refining mechanistic research.

Impact of healthy lifestyle on the incidence and progression trajectory of mental disorders: A prospective study in the UK Biobank

BACKGROUND

Healthier lifestyle decreased the risk of mental disorders (MDs) such as depression and anxiety. However, research on the effects of a comprehensive healthy lifestyle on their progression is lacking.

METHODS

385,704 individuals without baseline MDs from the UK Biobank cohort were included. A composite healthy lifestyle score was computed by assessing alcohol intake, smoking status, television viewing time, physical activity, sleep duration, fruit and vegetable intake, oily fish intake, red meat intake, and processed meat intake. Follow-up utilized hospital and death register records. Multistate model was used to examine the role of healthy lifestyle on the progression of specific MDs, while a piecewise Cox regression model was utilized to assess the influence of healthy lifestyle across various phases of disease progression.

RESULTS

Higher lifestyle score reduced risks of transitions from baseline to anxiety and depression, as well as from anxiety and depression to comorbidity, with corresponding hazard ratios (HR) and 95 % confidence intervals (CI) of 0.94 (0.93, 0.95), 0.90 (0.89, 0.91), 0.94 (0.91, 0.98), and 0.95 (0.92, 0.98), respectively. Healthier lifestyle decreased the risk of transitioning from anxiety to comorbidity within 2 years post-diagnosis, with HR 0.93 (0.88, 0.98). Higher lifestyle scores at 2-4 years and 4-6 years post-depression onset were associated with reduced risk of comorbidity, with HR 0.93 (0.87, 0.99) and 0.92 (0.86, 0.99), respectively.

LIMITATION

The generalizability to other ethnic groups is limited.

CONCLUSION

This study observed a protective role of holistic healthy lifestyle in the trajectory of MDs and contributed to identifying critical progression windows.

Eye-brain connections revealed by multimodal retinal and brain imaging genetics

The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

Disentangling differing relationships between internalizing disorders and alcohol use

Both internalizing disorders and alcohol use have dramatic, wide-spread implications for global health. Previous work has established common phenotypic comorbidity among these disorders, as well as shared genetic variation underlying them both. We used genomic structural equation modeling to investigate the shared genetics of internalizing, externalizing, and alcohol use traits, as well as to explore whether specific domains of internalizing symptoms mediate the contrasting relationships with problematic alcohol use compared to alcohol consumption. We also examined patterns of genetic correlations between similar traits within additional Finnish and East Asian ancestry groups. When the shared genetic influence of externalizing psychopathology was accounted for, the genetic effect of internalizing traits on alcohol use was reduced, suggesting the important role of common genetic factors underlying multiple psychiatric disorders and their genetic influences on comorbidity of internalizing and alcohol use traits. Individual internalizing domains had contrasting effects on frequency of alcohol consumption, which demonstrate the complex system of pleiotropy that exists, even within similar disorders, and can be missed when evaluating only relationships among formal diagnoses. Future work must consider the broad effects of shared psychopathology along with the fine-scale effects of heterogeneity within disorders to more fully understand the biology underlying complex traits.

Polygenic Analyses Show Important Differences Between Major Depressive Disorder Symptoms Measured Using Various Instruments

BACKGROUND

Symptoms of major depressive disorder (MDD) are commonly assessed using self-rating instruments like the Patient Health Questionnaire-9 (PHQ-9) (current symptoms) and the Composite International Diagnostic Interview Short-Form (CIDI-SF) (worst-episode symptoms). We performed a systematic comparison between them for their genetic architecture and utility in investigating MDD heterogeneity.

METHODS

Using data from the UK Biobank (n = 41,948-109,417), we assessed the single nucleotide polymorphism heritability and genetic correlation (rg) of both sets of MDD symptoms. We further compared their rg with non-MDD traits and used Mendelian randomization to assess whether either set of symptoms has more genetic sharing with non-MDD traits. We also assessed how specific each set of symptoms is to MDD using the metric polygenic risk score pleiotropy. Finally, we used genomic structural equation modeling to identify factors that explain the genetic covariance between each set of symptoms.

RESULTS

Corresponding symptoms reported through the PHQ-9 and CIDI-SF have low to moderate genetic correlations (rg = 0.43-0.87), and this cannot be fully attributed to different severity thresholds or the use of a skip structure in the CIDI-SF. Both Mendelian randomization and polygenic risk score pleiotropy analyses showed that PHQ-9 symptoms are more associated with traits that reflect general dysphoria, whereas the skip structure in the CIDI-SF allows for the identification of heterogeneity among likely MDD cases. Finally, the 2 sets of symptoms showed different factor structures in genomic structural equation modeling, reflective of their genetic differences.

CONCLUSIONS

MDD symptoms assessed using the PHQ-9 and CIDI-SF are not interchangeable; the former better indexes general dysphoria, while the latter is more informative about within-MDD heterogeneity.

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

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

Genetics of environmental sensitivity to psychiatric and neurodevelopmental phenotypes: evidence from GWAS of monozygotic twins

Individual sensitivity to environmental exposures may be genetically influenced. This genotype-by-environment interplay implies differences in phenotypic variance across genotypes. However, environmental sensitivity genetic variants have proven challenging to detect. GWAS of monozygotic twin differences is a family-based variance analysis method, which is more robust to systemic biases that impact population-based methods. We combined data from up to 21,792 monozygotic twins (10,896 pairs) from 11 studies to conduct the largest GWAS meta-analysis of monozygotic phenotypic differences in children and adolescents/adults for seven psychiatric and neurodevelopmental phenotypes: attention deficit hyperactivity disorder (ADHD) symptoms, autistic traits, anxiety and depression symptoms, psychotic-like experiences, neuroticism, and wellbeing. The SNP-heritability of variance in these phenotypes were estimated (h2: 0% to 18%), but were imprecise. We identified a total of 13 genome-wide significant associations (SNP, gene, and gene-set), including genes related to stress-reactivity for depression, growth factor-related genes for autistic traits and catecholamine uptake-related genes for psychotic-like experiences. Monozygotic twins are an important new source of evidence about the genetics of environmental sensitivity.

Unraveling COVID-19 relationship with anxiety disorders and symptoms using genome-wide data

BACKGROUND

There is still a limited understanding of the dynamics contributing to the comorbidity of COVID-19 and anxiety outcomes.

METHODS

To dissect the pleiotropic mechanisms contributing to COVID-19/anxiety comorbidity, we used genome-wide data from UK Biobank (up to 420,531 participants), FinnGen Project (up to 329,077 participants), Million Veteran Program (175,163 participants), and COVID-19 Host Genetics Initiative (up to 122,616 cases and 2,475,240 controls). Specifically, we assessed global and local genetic correlation and genetically inferred effects linking COVID-19 outcomes (infection, hospitalization, and severe respiratory symptoms) to anxiety disorders and symptoms.

RESULTS

We observed a strong genetic correlation of anxiety disorder with COVID-19 positive status (rg = 0.35, p = 2×10-4) and COVID-19 hospitalization (rg = 0.31, p = 7.2×10-4). Among anxiety symptoms, "Tense, sore, or aching muscles during worst period of anxiety" was genetically correlated with COVID-19 positive status (rg = 0.33, p = 0.001), while "Frequent trouble falling or staying asleep during worst period of anxiety" was genetically correlated with COVID-19 hospitalization (rg = 0.24, p = 0.004). Through a latent causal variable analysis, we observed that COVID-19 outcomes have statistically significant genetic causality proportion (gcp) on anxiety symptoms (e.g., COVID-19 positive status→"Recent easy annoyance or irritability" │gcp│ = 0.18, p = 6.72×10-17). Conversely, anxiety disorders appear to have a possible causal effect on COVID-19 (│gcp│ = 0.38, p = 3.17×10-9). Additionally, we also identified multiple loci with evidence of local genetic correlation between anxiety and COVID-19. These appear to be related to genetic effects shared with lung function, brain morphology, alcohol and tobacco use, and hematologic parameters.

CONCLUSIONS

This study provided insights into the pleiotropic mechanisms linking COVID-19 and anxiety outcomes, suggesting differences between dynamics related to anxiety disorders and those related to anxiety symptoms.

A cross-sectional study on the analysis of the current situation of depression and anxiety among primary and secondary school students in Urumqi City in 2021: A case study of S district

BACKGROUND

Depression and anxiety in children and adolescents have become one of the major public health threats. This study aimed to provide a comprehensive and accurate understanding of the current status of depression and anxiety in primary and secondary school students in Urumqi and to provide a basis for early intervention in depressed and anxious individuals.

METHODS

All primary and secondary school students in 13 schools in the Urumqi S district were surveyed from March 2021 to November 2021, and depression and anxiety were screened using the Self-rating Depression Scale (SDS) and the Self-rating Anxiety Scale (SAS).

RESULTS

Overall, 17,086 students participated, with 16,462 valid questionnaires and an effective rate of 96.3%; the numbers of primary, middle, and high school students were 3351, 10,469, and 2642, respectively, with 8493 male students and 7969 female students. The overall depression and anxiety detection rates of primary and secondary school students were 10.74 % and 14.85 %, respectively; the depression detection rates were 5.97 %, 12.05 %, and 11.62 % in elementary, middle, and high schools, respectively=114.8, P < 0.001), while that of anxiety were 9.16 %, 16.75 %, and 14.53 %, respectively (x2=127.5, P < 0.001); the overall depression combined with anxiety detection rate was 8.61 %, and the depression combined with anxiety detection rates in elementary, middle, and high school were 0.95 %, 6.27 %, and 1.39 %, respectively=86.34, P < 0.001). SDS scores in elementary, middle, and high school were (33.21 ± 10.16), (36.66 ± 12.83), and (36.90 ± 11.97), respectively, and SAS scores were (39.64 ± 8.41), (41.88 ± 10.03), (40.71 ± 9.26), respectively. The depression and anxiety scores of primary and secondary school students in Urumqi were lower than those of domestic norm; female students in the middle school group had the highest depression and anxiety scores among all school periods. The SDS and SAS individual scores showed differences in the frequency of specific symptoms and subjective feelings of depression and anxiety among students of different sex and school periods. Depression and anxiety detection rates were highest in secondary school and lowest in primary school; the detection rates of depression and anxiety were significantly higher in female students than in male students. Depression and anxiety scores were significantly lower in the primary school group than in the middle and high school groups, and depression and anxiety levels were significantly higher in female than in male students in each academic period. Female students were 2.045 (95 % confidence interval [CI]: 1.845-2.267) and 2.006 (95 % CI: 1.835-2.193) times more likely to have symptoms of depression and anxiety than male students, respectively. Middle school students were 7.112 (95 % CI: 3.639-13.898) and 5.499 (95 % CI: 3.302-9.155) times and high school students were 7.504(95 % CI: 3.740-15.058) and 5.093 (95 % CI: 2.966-8.744) times more likely to have symptoms of depression and anxiety than elementary school students, respectively.

LIMITATIONS

The pandemic may have impacted the results of the study, and this study did not explore the influencing factors of anxiety and depression.

CONCLUSION

Depression and anxiety symptoms exist in some primary and secondary school students in S District, Urumqi.

Identification and validation of supervariants reveal novel loci associated with human white matter microstructure

As an essential part of the central nervous system, white matter coordinates communications between different brain regions and is related to a wide range of neurodegenerative and neuropsychiatric disorders. Previous genome-wide association studies (GWASs) have uncovered loci associated with white matter microstructure. However, GWASs suffer from limited reproducibility and difficulties in detecting multi-single-nucleotide polymorphism (multi-SNP) and epistatic effects. In this study, we adopt the concept of supervariants, a combination of alleles in multiple loci, to account for potential multi-SNP effects. We perform supervariant identification and validation to identify loci associated with 22 white matter fractional anisotropy phenotypes derived from diffusion tensor imaging. To increase reproducibility, we use United Kingdom (UK) Biobank White British (n = 30,842) data for discovery and internal validation, and UK Biobank White but non-British (n = 1927) data, Europeans from the Adolescent Brain Cognitive Development study (n = 4399) data, and Europeans from the Human Connectome Project (n = 319) data for external validation. We identify 23 novel loci on the discovery set that have not been reported in the previous GWASs on white matter microstructure. Among them, three supervariants on genomic regions 5q35.1, 8p21.2, and 19q13.32 have P-values lower than 0.05 in the meta-analysis of the three independent validation data sets. These supervariants contain genetic variants located in genes that have been related to brain structures, cognitive functions, and neuropsychiatric diseases. Our findings provide a better understanding of the genetic architecture underlying white matter microstructure.

Genome-wide meta-analysis, functional genomics and integrative analyses implicate new risk genes and therapeutic targets for anxiety disorders

Anxiety disorders are the most prevalent mental disorders. However, the genetic etiology of anxiety disorders remains largely unknown. Here we conducted a genome-wide meta-analysis on anxiety disorders by including 74,973 (28,392 proxy) cases and 400,243 (146,771 proxy) controls. We identified 14 risk loci, including 10 new associations near CNTNAP5, MAP2, RAB9BP1, BTN1A1, PRR16, PCLO, PTPRD, FARP1, CDH2 and RAB27B. Functional genomics and fine-mapping pinpointed the potential causal variants, and expression quantitative trait loci analysis revealed the potential target genes regulated by the risk variants. Integrative analyses, including transcriptome-wide association study, proteome-wide association study and colocalization analyses, prioritized potential causal genes (including CTNND1 and RAB27B). Evidence from multiple analyses revealed possibly causal genes, including RAB27B, BTN3A2, PCLO and CTNND1. Finally, we showed that Ctnnd1 knockdown affected dendritic spine density and resulted in anxiety-like behaviours in mice, revealing the potential role of CTNND1 in anxiety disorders. Our study identified new risk loci, potential causal variants and genes for anxiety disorders, providing insights into the genetic architecture of anxiety disorders and potential therapeutic targets.

The genetic contribution to the comorbidity of depression and anxiety: a multi-site electronic health records study of almost 178 000 people

BACKGROUND

Depression and anxiety are common and highly comorbid, and their comorbidity is associated with poorer outcomes posing clinical and public health concerns. We evaluated the polygenic contribution to comorbid depression and anxiety, and to each in isolation.

METHODS

Diagnostic codes were extracted from electronic health records for four biobanks [N = 177 865 including 138 632 European (77.9%), 25 612 African (14.4%), and 13 621 Hispanic (7.7%) ancestry participants]. The outcome was a four-level variable representing the depression/anxiety diagnosis group: neither, depression-only, anxiety-only, and comorbid. Multinomial regression was used to test for association of depression and anxiety polygenic risk scores (PRSs) with the outcome while adjusting for principal components of ancestry.

RESULTS

In total, 132 960 patients had neither diagnosis (74.8%), 16 092 depression-only (9.0%), 13 098 anxiety-only (7.4%), and 16 584 comorbid (9.3%). In the European meta-analysis across biobanks, both PRSs were higher in each diagnosis group compared to controls. Notably, depression-PRS (OR 1.20 per s.d. increase in PRS; 95% CI 1.18-1.23) and anxiety-PRS (OR 1.07; 95% CI 1.05-1.09) had the largest effect when the comorbid group was compared with controls. Furthermore, the depression-PRS was significantly higher in the comorbid group than the depression-only group (OR 1.09; 95% CI 1.06-1.12) and the anxiety-only group (OR 1.15; 95% CI 1.11-1.19) and was significantly higher in the depression-only group than the anxiety-only group (OR 1.06; 95% CI 1.02-1.09), showing a genetic risk gradient across the conditions and the comorbidity.

CONCLUSIONS

This study suggests that depression and anxiety have partially independent genetic liabilities and the genetic vulnerabilities to depression and anxiety make distinct contributions to comorbid depression and anxiety.

Diagnostic Criteria for Identifying Individuals at High Risk of Progression From Mild or Moderate to Severe Alcohol Use Disorder

Importance

Current Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) diagnoses of substance use disorders rely on criterion count-based approaches, disregarding severity grading indexed by individual criteria.

Objective

To examine correlates of alcohol use disorder (AUD) across count-based severity groups (ie, mild, moderate, mild-to-moderate, severe), identify specific diagnostic criteria indicative of greater severity, and evaluate whether specific criteria within mild-to-moderate AUD differentiate across relevant correlates and manifest in greater hazards of severe AUD development.

Design, Setting, and Participants

This cohort study involved 2 cohorts from the family-based Collaborative Study on the Genetics of Alcoholism (COGA) with 7 sites across the United States: cross-sectional (assessed 1991-2005) and longitudinal (assessed 2004-2019). Statistical analyses were conducted from December 2022 to June 2023.

Main Outcomes and Measures

Sociodemographic, alcohol-related, psychiatric comorbidity, brain electroencephalography (EEG), and AUD polygenic score measures as correlates of DSM-5 AUD levels (ie, mild, moderate, severe) and criterion severity-defined mild-to-moderate AUD diagnostic groups (ie, low-risk vs high-risk mild-to-moderate).

Results

A total of 13 110 individuals from the cross-sectional COGA cohort (mean [SD] age, 37.8 [14.2] years) and 2818 individuals from the longitudinal COGA cohort (mean baseline [SD] age, 16.1 [3.2] years) were included. Associations with alcohol-related, psychiatric, EEG, and AUD polygenic score measures reinforced the role of increasing criterion counts as indexing severity. Yet within mild-to-moderate AUD (2-5 criteria), the presence of specific high-risk criteria (eg, withdrawal) identified a group reporting heavier drinking and greater psychiatric comorbidity even after accounting for criterion count differences. In longitudinal analyses, prior mild-to-moderate AUD characterized by endorsement of at least 1 high-risk criterion was associated with more accelerated progression to severe AUD (adjusted hazard ratio [aHR], 11.62; 95% CI, 7.54-17.92) compared with prior mild-to-moderate AUD without endorsement of high-risk criteria (aHR, 5.64; 95% CI, 3.28-9.70), independent of criterion count.

Conclusions and Relevance

In this cohort study of a combined 15 928 individuals, findings suggested that simple count-based AUD diagnostic approaches to estimating severe AUD vulnerability, which ignore heterogeneity among criteria, may be improved by emphasizing specific high-risk criteria. Such emphasis may allow better focus on individuals at the greatest risk and improve understanding of the development of AUD.

Characterizing the phenotypic and genetic structure of psychopathology in UK Biobank

Mental conditions exhibit a higher-order transdiagnostic factor structure which helps to explain the widespread comorbidity observed in psychopathology. However, the phenotypic and genetic structures of psychopathology may differ, raising questions about the validity and utility of these factors. Here, we study the phenotypic and genetic factor structures of ten psychiatric conditions using UK Biobank and public genomic data. Although the factor structure of psychopathology was generally genetically and phenotypically consistent, conditions related to externalizing (e.g., alcohol use disorder) and compulsivity (e.g., eating disorders) exhibited cross-level disparities in their relationships with other conditions, plausibly due to environmental influences. Domain-level factors, especially thought disorder and internalizing factors, were more informative than a general psychopathology factor in genome-wide association and polygenic index analyses. Collectively, our findings enhance the understanding of comorbidity and shared etiology, highlight the intricate interplay between genes and environment, and offer guidance for psychiatric research using polygenic indices.

Identification of drug repurposing candidates for the treatment of anxiety: A genetic approach

Anxiety disorders are a group of prevalent and heritable neuropsychiatric diseases. We previously conducted a genome-wide association study (GWAS) which identified genomic loci associated with anxiety; however, the biological consequences underlying the genetic associations are largely unknown. Integrating GWAS and functional genomic data may improve our understanding of the genetic effects on intermediate molecular phenotypes such as gene expression. This can provide an opportunity for the discovery of drug targets for anxiety via drug repurposing. We used the GWAS summary statistics to determine putative causal genes for anxiety using MAGMA and colocalization analyses. A transcriptome-wide association study was conducted to identify genes with differential genetically regulated levels of gene expression in human brain tissue. The genes were integrated with a large drug-gene expression database (Connectivity Map), discovering compounds that are predicted to "normalise" anxiety-associated expression changes. The study identified 64 putative causal genes associated with anxiety (35 genes upregulated; 29 genes downregulated). Drug mechanisms adrenergic receptor agonists, sigma receptor agonists, and glutamate receptor agonists gene targets were enriched in anxiety-associated genetic signal and exhibited an opposing effect on the anxiety-associated gene expression signature. The significance of the project demonstrated genetic links for novel drug candidates to potentially advance anxiety therapeutics.

Methylome-wide association study of anxiety disorders

Anxiety Disorders (ANX) such as panic disorder, generalized anxiety disorder, and phobias, are highly prevalent conditions that are moderately heritable. Evidence suggests that DNA methylation may play a role, as it is involved in critical adaptations to changing environments. Applying an enrichment-based sequencing approach covering nearly 28 million autosomal CpG sites, we conducted a methylome-wide association study (MWAS) of lifetime ANX in 1132 participants (618 cases/514 controls) from the Netherlands Study of Depression and Anxiety. Using epigenomic deconvolution, we performed MWAS for the main cell types in blood: granulocytes, T-cells, B-cells and monocytes. Cell-type specific analyses identified 280 and 82 methylome-wide significant associations (q-value < 0.1) in monocytes and granulocytes, respectively. Our top finding in monocytes was located in ZNF823 on chromosome 19 (p = 1.38 × 10-10) previously associated with schizophrenia. We observed significant overlap (p < 1 × 10-06) with the same direction of effect in monocytes (210 sites), T-cells (135 sites), and B-cells (727 sites) between this Discovery MWAS signal and a comparable replication dataset from the Great Smoky Mountains Study (N = 433). Overlapping Discovery-Replication MWAS signal was enriched for findings from published GWAS of ANX, major depression, and post-traumatic stress disorder. In monocytes, two specific sites in the FZR1 gene showed significant replication after Bonferroni correction with an additional 15 nominally replicated sites in monocytes and 4 in T-cells. FZR1 regulates neurogenesis in the hippocampus, and its knockout leads to impairments in associative fear memory and long-term potentiation in mice. In the largest and most extensive methylome-wide study of ANX, we identified replicable methylation sites located in genes of potential relevance for brain mechanisms of psychiatric conditions.

Unraveling COVID-19 Relationship with Anxiety Disorders and Symptoms

Background

While COVID-19 outcomes are associated with increased anxiety, individuals affected by anxiety disorders are more likely to develop severe COVID-19 outcomes.

Methods

We used genome-wide data from UK Biobank (up to 420,531 participants), FinnGen Project (up to 329,077 participants), Million Veteran Program (175,163 participants), and COVID-19 Host Genetics Initiative (up to 122,616 cases and 2,475,240 controls) to investigate possible causal effects and shared genetic mechanisms linking COVID-19 outcomes to anxiety disorders and symptoms.

Results

We observed a strong genetic correlation of anxiety disorder with COVID-19 positive status (rg=0.35, p=2 × 10 -4 ) and COVID-19 hospitalization (rg=0.31, p=7.2 × 10 -4 ). Among anxiety symptoms, "Tense, sore, or aching muscles during worst period of anxiety" was genetically correlated with COVID-19 positive status (rg=0.33, p=0.001), while "Frequent trouble falling or staying asleep during worst period of anxiety" was genetically correlated with COVID-19 hospitalization (rg=0.24, p=0.004). Through a latent causal variable analysis, we observed that COVID-19 outcomes have statistically significant genetic causality proportion (gcp) on anxiety symptoms (e.g., COVID-19 positive status→"Recent easy annoyance or irritability" │gcp│=0.18, p=6.72 × 10 -17 ). Conversely, anxiety disorders appear to have a possible causal effect on COVID-19 (│gcp│=0.38, p=3.17 × 10 -9 ). Additionally, we also identified multiple loci with evidence of local genetic correlation between anxiety and COVID-19. These appear to be related to genetic effects shared with lung function, brain morphology, alcohol and tobacco use, and hematologic parameters.

Conclusions

This study provided important insights into the relationship between COVID-19 and mental health, differentiating the dynamics linking anxiety disorders to COVID-19 from the effect of COVID-19 on anxiety symptoms.

Identification of a psychiatric risk gene NISCH at 3p21.1 GWAS locus mediating dendritic spine morphogenesis and cognitive function

BACKGROUND

Schizophrenia and bipolar disorder (BD) are believed to share clinical symptoms, genetic risk, etiological factors, and pathogenic mechanisms. We previously reported that single nucleotide polymorphisms spanning chromosome 3p21.1 showed significant associations with both schizophrenia and BD, and a risk SNP rs2251219 was in linkage disequilibrium with a human specific Alu polymorphism rs71052682, which showed enhancer effects on transcriptional activities using luciferase reporter assays in U251 and U87MG cells.

METHODS

CRISPR/Cas9-directed genome editing, real-time quantitative PCR, and public Hi-C data were utilized to investigate the correlation between the Alu polymorphism rs71052682 and NISCH. Primary neuronal culture, immunofluorescence staining, co-immunoprecipitation, lentiviral vector production, intracranial stereotaxic injection, behavioral assessment, and drug treatment were used to examine the physiological impacts of Nischarin (encoded by NISCH).

RESULTS

Deleting the Alu sequence in U251 and U87MG cells reduced mRNA expression of NISCH, the gene locates 180 kb from rs71052682, and Hi-C data in brain tissues confirmed the extensive chromatin contacts. These data suggested that the genetic risk of schizophrenia and BD predicted elevated NISCH expression, which was also consistent with the observed higher NISCH mRNA levels in the brain tissues from psychiatric patients compared with controls. We then found that overexpression of NISCH resulted in a significantly decreased density of mushroom dendritic spines with a simultaneously increased density of thin dendritic spines in primary cultured neurons. Intriguingly, elevated expression of this gene in mice also led to impaired spatial working memory in the Y-maze. Given that Nischarin is the target of anti-hypertensive agents clonidine and tizanidine, which have shown therapeutic effects in patients with schizophrenia and patients with BD in preliminary clinical trials, we demonstrated that treatment with those antihypertensive drugs could reduce NISCH mRNA expression and rescue the impaired working memory in mice.

CONCLUSIONS

We identify a psychiatric risk gene NISCH at 3p21.1 GWAS locus influencing dendritic spine morphogenesis and cognitive function, and Nischarin may have potentials for future therapeutic development.

A multivariate genome-wide association study of psycho-cardiometabolic multimorbidity

Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity (Neffective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately genetically correlated with T2D (rg = 0.39, P = 2e-34) and weakly correlated with depression (rg = 0.13, P = 3e-6). Depression was weakly correlated with T2D (rg = 0.15, P = 4e-15). The latent multimorbidity factor explained the largest proportion of variance in T2D (45%), followed by CAD (35%) and depression (5%). We identified 11 independent SNPs associated with multimorbidity and 18 putative multimorbidity-associated genes. We observed enrichment in immune and inflammatory pathways. A greater polygenic risk score for multimorbidity in the UK Biobank (N = 306,734) was associated with the co-occurrence of CAD, T2D and depression (OR per standard deviation = 1.91, 95% CI = 1.74-2.10, relative to the healthy group), validating this latent multimorbidity factor. Mendelian randomization analyses suggested potentially causal effects of BMI, body fat percentage, LDL cholesterol, total cholesterol, fasting insulin, income, insomnia, and childhood maltreatment. These findings advance our understanding of multimorbidity suggesting common genetic pathways.

CADM2 is implicated in impulsive personality and numerous other traits by genome- and phenome-wide association studies in humans and mice

Impulsivity is a multidimensional heritable phenotype that broadly refers to the tendency to act prematurely and is associated with multiple forms of psychopathology, including substance use disorders. We performed genome-wide association studies (GWAS) of eight impulsive personality traits from the Barratt Impulsiveness Scale and the short UPPS-P Impulsive Personality Scale (N = 123,509-133,517 23andMe research participants of European ancestry), and a measure of Drug Experimentation (N = 130,684). Because these GWAS implicated the gene CADM2, we next performed single-SNP phenome-wide studies (PheWAS) of several of the implicated variants in CADM2 in a multi-ancestral 23andMe cohort (N = 3,229,317, European; N = 579,623, Latin American; N = 199,663, African American). Finally, we produced Cadm2 mutant mice and used them to perform a Mouse-PheWAS ("MouseWAS") by testing them with a battery of relevant behavioral tasks. In humans, impulsive personality traits showed modest chip-heritability (~6-11%), and moderate genetic correlations (rg = 0.20-0.50) with other personality traits, and various psychiatric and medical traits. We identified significant associations proximal to genes such as TCF4 and PTPRF, and also identified nominal associations proximal to DRD2 and CRHR1. PheWAS for CADM2 variants identified associations with 378 traits in European participants, and 47 traits in Latin American participants, replicating associations with risky behaviors, cognition and BMI, and revealing novel associations including allergies, anxiety, irritable bowel syndrome, and migraine. Our MouseWAS recapitulated some of the associations found in humans, including impulsivity, cognition, and BMI. Our results further delineate the role of CADM2 in impulsivity and numerous other psychiatric and somatic traits across ancestries and species.

Exploratory factor analysis of shared and specific genetic associations in depression and anxiety

BACKGROUND

Previous genetic studies of anxiety and depression were mostly based on independent phenotypes. This study aims to investigate the shared and specific genetic structure between anxiety and depression.

METHOD

To identify the underlying factors of Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), and their combined scale (joint scale), we employed exploratory factor analysis (EFA) using the eigenvalue of parallel analysis. Subsequently, we conducted a genome-wide association study (GWAS) for these factors. In addition, we utilized LD Score Regression (LDSC) to determine the genetic correlations between the identified factors and four common mental disorders, three sleep phenotypes, and other traits that have been previously linked to anxiety and depression.

RESULTS

The EFA uncovered two factors for the GAD-7 scale, namely nervousness and disturbance, two factors for the PHQ-9 scale, namely negative affect and sleep/appetite disturbance, and four factors for the joint scale, specifically nervousness, anhedonia, sleep/appetite disturbance, and fidget. We identified two genome-wide significant genomic loci, with overlap across GAD-7 factor 1 and joint scale factor 1: rs148579586 (P_GAD-7 = 1.365 × 10^-09, P_{Joint scale} = 1.434 × 1^0-09) and rs201074060 (P_GAD-7 = 3.672 × 10^-09, P_{Joint scale} = 3.824 × 10^-09). Genetic correlations in factors ranged from 0.722 to 1.000 (all p < 1.786 × 10^-3) with 27 of 28 correlations being significantly smaller than one. The genetic correlations with external phenotypes showed small variation across the eight factors.

CONCLUSION

Unidimensional structures can provide more precise scores, which can aid in identifying the shared and specific genetic associations between anxiety and depression. This is a crucial step in characterizing the genetic structure of these conditions and their co-occurrence.

Genotype determining aerobic exercise capacity associates with behavioral plasticity in middle-aged rats

Good aerobic fitness associates positively with cognitive performance and brain health and conversely, low aerobic fitness predisposes to neurodegenerative diseases. To study how genotype together with exercise, started at older age, affects brain and behavior, we utilized rats that differ in inherited aerobic fitness. Rats bred for Low Capacity for Running (LCR) are shown to display less synaptic plasticity and more inflammation in the hippocampus and perform worse than rats bred for a High Capacity for Running (HCR) in tasks requiring flexible cognition. Here we used middle-aged (∼ 16 months) HCR and LCR rats to study how genotype and sex associate with anxiety and neural information filtering, termed sensory gating. Further, we assessed how inherited aerobic capacity associates with hippocampus-dependent learning, measured with contextual fear conditioning task. In females, we also investigated the effects of voluntary wheel running (5 weeks) on these characteristics. Our results indicate that independent of sex or voluntary running, HCR rats were more anxious in open-field tasks, exhibited lower sensory gating and learned more efficiently in contextual fear conditioning task than LCR rats. Voluntary running did not markedly affect innate behavior but slightly decreased the differences between female LCR and HCR rats in fear learning. In conclusion, inherited fitness seems to determine cognitive and behavioral traits independent of sex. Although the traits proved to be rather resistant to change at adult age, learning was slightly improved following exercise in LCR females, prone to obesity and poor fitness.

Examining the shared etiology of psychopathology with genome-wide association studies

Genome-wide association studies (GWASs) have ushered in a new era of reproducible discovery in psychiatric genetics. The field has now identified hundreds of common genetic variants that are associated with mental disorders, and many of them influence more than one disorder. By advancing the understanding of causal biology underlying psychopathology, GWAS results are poised to inform the development of novel therapeutics, stratification of at-risk patients, and perhaps even the revision of top-down classification systems in psychiatry. Here, we provide a concise review of GWAS findings with an emphasis on findings that have elucidated the shared genetic etiology of psychopathology, summarizing insights at three levels of analysis: 1) genome-wide architecture; 2) networks, pathways, and gene sets; and 3) individual variants/genes. Three themes emerge from these efforts. First, all psychiatric phenotypes are heritable, highly polygenic, and influenced by many pleiotropic variants with incomplete penetrance. Second, GWAS results highlight the broad etiological roles of neuronal biology, system-wide effects over localized effects, and early neurodevelopment as a critical period. Third, many loci that are robustly associated with multiple forms of psychopathology harbor genes that are involved in synaptic structure and function. Finally, we conclude our review by discussing the implications that GWAS results hold for the field of psychiatry, as well as expected challenges and future directions in the next stage of psychiatric genetics.

Polygenic analyses show important differences between MDD symptoms collected using PHQ9 and CIDI-SF

Symptoms of Major Depressive Disorder (MDD) are commonly assessed using self-rating instruments like the Patient Health Questionnaire 9 (PHQ9, for current symptoms), and the Composite International Diagnostic Interview Short-Form (CIDI-SF, for lifetime worst-episode symptoms). Using data from the UKBiobank, we show that corresponding symptoms endorsed through PHQ9 and CIDI-SF have low to moderate genetic correlations (rG=0.43-0.87), and this cannot be fully attributed to different severity thresholds or the use of a skip-structure in CIDI-SF. Through a combination of Mendelian Randomization (MR) and polygenic prediction analyses, we find that PHQ9 symptoms are more associated with traits which reflect general dysphoria, while the skip-structure in CIDI-SF allows for the identification of heterogeneity among likely MDD cases. This has important implications on factor analyses performed on their respective genetic covariance matrices for the purpose of identification of genetic factors behind MDD symptom dimensions and heterogeneity.

Genetic architecture of the white matter connectome of the human brain

White matter tracts form the structural basis of large-scale brain networks. We applied brain-wide tractography to diffusion images from 30,810 adults (U.K. Biobank) and found significant heritability for 90 node-level and 851 edge-level network connectivity measures. Multivariate genome-wide association analyses identified 325 genetic loci, of which 80% had not been previously associated with brain metrics. Enrichment analyses implicated neurodevelopmental processes including neurogenesis, neural differentiation, neural migration, neural projection guidance, and axon development, as well as prenatal brain expression especially in stem cells, astrocytes, microglia, and neurons. The multivariate association profiles implicated 31 loci in connectivity between core regions of the left-hemisphere language network. Polygenic scores for psychiatric, neurological, and behavioral traits also showed significant multivariate associations with structural connectivity, each implicating distinct sets of brain regions with trait-relevant functional profiles. This large-scale mapping study revealed common genetic contributions to variation in the structural connectome of the human brain.

Eye-brain connections revealed by multimodal retinal and brain imaging genetics in the UK Biobank

As an anatomical extension of the brain, the retina of the eye is synaptically connected to the visual cortex, establishing physiological connections between the eye and the brain. Despite the unique opportunity retinal structures offer for assessing brain disorders, less is known about their relationship to brain structure and function. Here we present a systematic cross-organ genetic architecture analysis of eye-brain connections using retina and brain imaging endophenotypes. Novel phenotypic and genetic links were identified between retinal imaging biomarkers and brain structure and function measures derived from multimodal magnetic resonance imaging (MRI), many of which were involved in the visual pathways, including the primary visual cortex. In 65 genomic regions, retinal imaging biomarkers shared genetic influences with brain diseases and complex traits, 18 showing more genetic overlaps with brain MRI traits. Mendelian randomization suggests that retinal structures have bidirectional genetic causal links with neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, cross-organ imaging genetics reveals a genetic basis for eye-brain connections, suggesting that the retinal images can elucidate genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

Alternative polyadenylation transcriptome-wide association study identifies APA-linked susceptibility genes in brain disorders

Alternative polyadenylation (APA) plays an essential role in brain development; however, current transcriptome-wide association studies (TWAS) largely overlook APA in nominating susceptibility genes. Here, we performed a 3' untranslated region (3'UTR) APA TWAS (3'aTWAS) for 11 brain disorders by combining their genome-wide association studies data with 17,300 RNA-seq samples across 2,937 individuals. We identified 354 3'aTWAS-significant genes, including known APA-linked risk genes, such as SNCA in Parkinson's disease. Among these 354 genes, ~57% are not significant in traditional expression- and splicing-TWAS studies, since APA may regulate the translation, localization and protein-protein interaction of the target genes independent of mRNA level expression or splicing. Furthermore, we discovered ATXN3 as a 3'aTWAS-significant gene for amyotrophic lateral sclerosis, and its modulation substantially impacted pathological hallmarks of amyotrophic lateral sclerosis in vitro. Together, 3'aTWAS is a powerful strategy to nominate important APA-linked brain disorder susceptibility genes, most of which are largely overlooked by conventional expression and splicing analyses.

Genetic Liabilities Differentiating Bipolar Disorder, Schizophrenia, and Major Depressive Disorder, and Phenotypic Heterogeneity in Bipolar Disorder

Importance

Understanding the origins of clinical heterogeneity in bipolar disorder (BD) will inform new approaches to stratification and studies of underlying mechanisms.

Objective

To identify components of genetic liability that are shared between BD, schizophrenia, and major depressive disorder (MDD) and those that differentiate each disorder from the others and to examine associations between heterogeneity for key BD symptoms and each component.

Design, Setting, and Participants

Using data from the Bipolar Disorder Research Network in the United Kingdom, components of liability were identified by applying genomic structural equation modeling to genome-wide association studies of schizophrenia, BD, and MDD. Polygenic risk scores (PRS) representing each component were tested for association with symptoms in an independent BD data set. Adults with DSM-IV BD or schizoaffective disorder, bipolar type, were included. Data were collected from January 2000 to December 2013, and data were analyzed from June 2020 to February 2022.

Main Outcomes and Measures

PRS representing the components of liability were tested for association with mania and depression, psychosis, and mood incongruence of psychosis in participants with BD, measured using the Bipolar Affective Disorder Dimensional Scale.

Results

Of 4429 included participants, 3012 (68.0%) were female, and the mean (SD) age was 46.2 (12.3) years. Mania and psychosis were associated with the shared liability component (mania β = 0.29; 95% CI, 0.23-0.34; P = 3.04 × 10-25; psychosis β = 0.05; 95% CI, 0.04-0.07; P = 2.33 × 10-13) and the components that differentiate each of schizophrenia (mania β = 0.08; 95% CI, 0.03-0.14; P = .002; psychosis β = 0.03; 95% CI, 0.01-0.04; P = 1.0 × 10-4) and BD (mania β = 0.14; 95% CI, 0.09-0.20; P = 1.99 × 10-7; psychosis β = 0.02; 95% CI, 0.01-0.03; P = .006) from the other disorders. The BD differentiating component was associated with mania independently of effects on psychosis (β = 0.14; 95% CI, 0.08-0.20; P = 4.32 × 10-6) but not with psychosis independently of mania. Conversely, the schizophrenia differentiating component was associated with psychosis independently of effects on mania (β = 0.01; 95% CI, 0.003-0.03; P = .02), but not with mania independently of psychosis. Mood incongruence of psychosis was associated only with the schizophrenia differentiating component (β = 0.03; 95% CI, 0.01-0.05; P = .005). Depression was associated with higher MDD differentiating component (β = 0.07; 95% CI, 0.01-0.12; P = .01) but lower BD differentiating component (β = -0.11; 95% CI, -0.17 to -0.06; P = 7.06 × 10-5).

Conclusions and Relevance

In this study of BD, clinical heterogeneity reflected the burden of liability to BD and the contribution of alleles that have differentiating effects on risk for other disorders; mania, psychosis, and depression were associated with the components of genetic liability differentiating BD, MDD, and schizophrenia, respectively. Understanding the basis of this etiological heterogeneity will be critical for identifying the different pathophysiological processes underlying BD, stratifying patients, and developing precision therapeutics.

A Local Genetic Correlation Analysis Provides Biological Insights Into the Shared Genetic Architecture of Psychiatric and Substance Use Phenotypes

BACKGROUND

Global genetic correlation analysis has provided valuable insight into the shared genetic basis between psychiatric and substance use disorders. However, little is known about which regions disproportionately contribute to the global correlation.

METHODS

We used Local Analysis of [co]Variant Annotation to calculate bivariate local genetic correlations across 2495 approximately equal-sized, semi-independent genomic regions for 20 psychiatric and substance use phenotypes. We performed a transcriptome-wide association study using expression weights from the prefrontal cortex to identify risk genes for each phenotype, followed by probabilistic fine-mapping to prioritize credible causal genes within each bivariate locus.

RESULTS

We detected 80 significant (p < 2.08 × 10-6) bivariate local genetic correlations across 61 loci. The expression effect directions for risk genes within each bivariate locus were largely consistent with the local correlation coefficients, suggesting that genetically regulated gene expression may be used in the functional interpretation of local genetic correlations. Probabilistic fine-mapping identified several genes that may drive pleiotropic mechanisms for genetically correlated phenotypes. For example, we confirmed a local genetic correlation between schizophrenia and smoking behavior at 15q25 and prioritized PSMA4 as the most credible gene candidate underlying both phenotypes.

CONCLUSIONS

Our study reveals previously unreported local bivariate genetic correlations between psychiatric and substance use phenotypes, which we fine-mapped to identify shared credible causal genes underlying genetically correlated phenotypes.

Ten challenges for clinical translation in psychiatric genetics

Genome-wide association studies have identified hundreds of robust genetic associations underlying psychiatric disorders and provided important biological insights into disease onset and progression. There is optimism that genetic findings will pave the way to precision psychiatry by facilitating the development of more effective treatments and the identification of groups of patients that these treatments should be targeted toward. However, there are several challenges that must be addressed before genetic findings can be translated into the clinic. In this Perspective, we highlight ten challenges for the field of psychiatric genetics, focused on the robust and generalizable detection of genetic risk factors, improved definition and assessment of psychopathology and achieving better clinical indicators. We discuss recent advancements in the field that will improve the explanatory and predictive power of genetic data and ultimately contribute to improving the management and treatment of patients with a psychiatric disorder.

Spatiotemporal Dynamics of Stress-Induced Network Reconfigurations Reflect Negative Affectivity

BACKGROUND

Maladaptive stress responses are important risk factors in the etiology of mood and anxiety disorders, but exact pathomechanisms remain to be understood. Mapping individual differences of acute stress-induced neurophysiological changes, especially on the level of neural activation and functional connectivity (FC), could provide important insights in how variation in the individual stress response is linked to disease risk.

METHODS

Using an established psychosocial stress task flanked by two resting states, we measured subjective, physiological, and brain responses to acute stress and recovery in 217 participants with and without mood and anxiety disorders. To estimate blockwise changes in stress-induced activation and FC, we used hierarchical mixed-effects models based on denoised time series within predefined stress-related regions. We predicted inter- and intraindividual differences in stress phases (anticipation vs. stress vs. recovery) and transdiagnostic dimensions of stress reactivity using elastic net and support vector machines.

RESULTS

We identified four subnetworks showing distinct changes in FC over time. FC but not activation trajectories predicted the stress phase (accuracy = 70%, p_perm < .001) and increases in heart rate (R² = 0.075, p_perm < .001). Critically, individual spatiotemporal trajectories of changes across networks also predicted negative affectivity (ΔR² = 0.075, p_perm = .030) but not the presence or absence of a mood and anxiety disorder.

CONCLUSIONS

Spatiotemporal dynamics of brain network reconfiguration induced by stress reflect individual differences in the psychopathology dimension of negative affectivity. These results support the idea that vulnerability for mood and anxiety disorders can be conceptualized best at the level of network dynamics, which may pave the way for improved prediction of individual risk.

Phenome-wide screening of the putative causal determinants of depression using genetic data

Depression is one of the most common mental health disorders and one of the top causes of disability throughout the world. The present study sought to identify putative causal associations between depression and hundreds of complex human traits through a genome-wide screening of genetic data and a hypothesis-free approach. We leveraged genome-wide association studies (GWAS) summary statistics for depression and 1504 complex traits and investigated potential causal relationships using the latent causal variable method. We identified 559 traits genetically correlated with depression risk at FDR < 5%. Of these, 46 were putative causal genetic determinants of depression, including lifestyle factors, diseases of the nervous system, respiratory disorders, diseases of the musculoskeletal system, traits related to the health of the gastrointestinal system, obesity, vitamin D levels, and the use of prescription medications, among others. No phenotypes were identified as potential outcomes of depression. Our results suggest that genetic liability to multiple complex traits may contribute to a higher risk for depression. In particular, we show a putative causal genetic effect of pain, obesity, and inflammation on depression. These findings provide novel insights into the potential causal determinants of depression and should be interpreted as testable hypotheses for future studies to confirm, which may facilitate the design of new prevention strategies to reduce depression's burden.

Serotonin Receptor and Transporter Endocytosis Is an Important Factor in the Cellular Basis of Depression and Anxiety

Depression and anxiety are common, debilitating psychiatric conditions affecting millions of people throughout the world. Current treatments revolve around selective serotonin reuptake inhibitors (SSRIs), yet these drugs are only moderately effective at relieving depression. Moreover, up to 30% of sufferers are SSRI non-responders. Endocytosis, the process by which plasma membrane and extracellular constituents are internalized into the cell, plays a central role in the regulation of serotonin (5-hydroxytryptophan, 5-HT) signaling, SSRI function and depression and anxiety pathogenesis. Despite their therapeutic potential, surprisingly little is known about the endocytosis of the serotonin receptors (5-HT receptors) or the serotonin transporter (SERT). A subset of 5-HT receptors are endocytosed by clathrin-mediated endocytosis following serotonin binding, while for the majority of 5-HT receptors the endocytic regulation is not known. SERT internalizes serotonin from the extracellular space into the cell to limit the availability of serotonin for receptor binding and signaling. Endocytosis of SERT reduces serotonin uptake, facilitating serotonin signaling. SSRIs predominantly inhibit SERT, preventing serotonin uptake to enhance 5-HT receptor signaling, while hallucinogenic compounds directly activate specific 5-HT receptors, altering their interaction with endocytic adaptor proteins to induce alternate signaling outcomes. Further, multiple polymorphisms and transcriptional/proteomic alterations have been linked to depression, anxiety, and SSRI non-response. In this review, we detail the endocytic regulation of 5-HT receptors and SERT and outline how SSRIs and hallucinogenic compounds modulate serotonin signaling through endocytosis. Finally, we will examine the deregulated proteomes in depression and anxiety and link these with 5-HT receptor and SERT endocytosis. Ultimately, in attempting to integrate the current studies on the cellular biology of depression and anxiety, we propose that endocytosis is an important factor in the cellular basis of depression and anxiety. We will highlight how a thorough understanding 5-HT receptor and SERT endocytosis is integral to understanding the biological basis of depression and anxiety, and to facilitate the development of a next generation of specific, efficacious antidepressant treatments.

Proteomic Insights Into Susceptibility and Resistance to Chronic-Stress-Induced Depression or Anxiety in the Rat Striatum

Chronic stress is a key factor for the onset of anxiety and depression disorders. However, the stress-induced common and unique molecular basis of the two psychiatric disorders is not fully known and still needs to be explored. Previously, we employed a chronic mild stress (CMS) procedure to induce a rat model including depression-susceptible (Dep-Sus), anxiety-susceptible (Anx-Sus), and insusceptible (Insus) cohorts. In this work, we continuously analyze the striatal proteomes of the three stressed cohorts by the use of comparative proteomics and bioinformatics approaches. Through isobaric tags for relative and absolute quantitation (iTRAQ)-based analysis, 386 abnormally expressed proteins in total were identified. These deregulated proteins are involved in various biological functions and significant pathways that are potentially connected with resistance and susceptibility to CMS-caused anxious- or depressive-like behaviors and, hence, could act as suggestive protein targets. A further parallel reaction monitoring-based independent investigation shows that alterations in Pak5, Dgkg, Scn4b, Rb1cc1, and Acin1; Ggps1, Fntb, Nudt19, Ufd1, and Ndufab1; and Dnajb12, Hbb2, Ap2s1, Ip6k1, and Stk4 were specifically connected with Dep-Sus, Anx-Sus, or Insus groups, respectively, potentially indicating that identical CMS treatment results in the different changes in the striatal protein regulations. Overall, our current proteomics study of the striatum provides an important molecular foundation and comprehensive insights into common and specific deregulations correlated with pathophysiological mechanisms that underlie resistance and susceptibility to chronic stress-induced anxiety or depression.

Proteomic Response of Rat Pituitary Under Chronic Mild Stress Reveals Insights Into Vulnerability and Resistance to Anxiety or Depression

Chronic stress as one of the most significant risk factor can trigger overactivity of hypothalamic-pituitary-adrenal (HPA) axis in depression as well as anxiety. Yet, the shared and unique neurobiological underpinnings underlying the pituitary abnormality in these two disorders have not been made clear. We previously have established depression-susceptible, anxiety-susceptible and insusceptible groups using a valid chronic mild stress (CMS) model. In this work, the possible protein expression changes in the rat pituitary of these three groups were continuously investigated through the use of the comparative quantitative proteomics and bioinformatics approaches. The pituitary-proteome analysis identified totally 197 differential proteins as a CMS response. These deregulated proteins were involved in diverse biological functions and significant pathways potentially connected with the three different behavioral phenotypes, likely serving as new investigative protein targets. Afterwards, parallel reaction monitoring-based independent analysis found out that expression alterations in Oxct1, Sec24c, Ppp1cb, Dock1, and Coq3; Lama1, Glb1, Gapdh, Sccpdh, and Renbp; Sephs1, Nup188, Spp1, Prodh1, and Srm were specifically linked to depression-susceptible, anxiety-susceptible and insusceptible groups, respectively, suggesting that the same CMS had different impacts on the pituitary protein regulatory system. Collectively, the current proteomics research elucidated an important molecular basis and furnished new valuable insights into neurochemical commonalities and specificities of the pituitary dysfunctional mechanisms in HPA axis underlying vulnerability and resistance to stress-induced anxiety or depression.

Vitamin D and the Risks of Depression and Anxiety: An Observational Analysis and Genome-Wide Environment Interaction Study

Previous studies have suggested that vitamin D (VD) was associated with psychiatric diseases, but efforts to elucidate the functional relevance of VD with depression and anxiety from genetic perspective have been limited. Based on the UK Biobank cohort, we first calculated polygenic risk score (PRS) for VD from genome-wide association study (GWAS) data of VD. Linear and logistic regression analysis were conducted to evaluate the associations of VD traits with depression and anxiety traits, respectively. Then, using individual genotype and phenotype data from the UK Biobank, genome-wide environment interaction studies (GWEIS) were performed to identify the potential effects of gene × VD interactions on the risks of depression and anxiety traits. In the UK Biobank cohort, we observed significant associations of blood VD level with depression and anxiety traits, as well as significant associations of VD PRS and depression and anxiety traits. GWEIS identified multiple candidate loci, such as rs114086183 (p = 4.11 × 10⁻⁸, LRRTM4) for self-reported depression status and rs149760119 (p = 3.88 × 10⁻⁸, GNB5) for self-reported anxiety status. Our study results suggested that VD was negatively associated with depression and anxiety. GWEIS identified multiple candidate genes interacting with VD, providing novel clues for understanding the biological mechanism potential associations between VD and psychiatric disorders.