Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways

Predicting Future Depressive Episodes from Resting-State fMRI with Generative Embedding

After a first episode of major depressive disorder (MDD), there is substantial risk for a long-term remitting-relapsing course. Prevention and early interventions are thus critically important. Various studies have examined the feasibility of detecting at-risk individuals based on out-of-sample predictions about the future occurrence of depression. However, functional magnetic resonance imaging (MRI) has received very little attention for this purpose so far. Here, we explored the utility of generative models (i.e. different dynamic causal models, DCMs) as well as functional connectivity (FC) for predicting future episodes of depression in never-depressed adults, using a large dataset (N=906) of task-free ("resting state") fMRI data from the UK Biobank. Connectivity analyses were conducted using timeseries from pre-computed spatially independent components of different dimensionalities. Over a three year period, 50% of participants showed indications of at least one depressive episode, while the other 50% did not. Using nested cross-validation for training and a held-out test set (80/20 split), we systematically examined the combination of 8 connectivity feature sets and 17 classifiers. We found that a generative embedding procedure based on combining regression DCM (rDCM) with a support vector machine (SVM) enabled the best predictions, both on the training set (0.63 accuracy, 0.66 area under the curve, AUC) and the test set (0.62 accuracy, 0.64 AUC; p<0.001). However, on the test set, rDCM was only slightly superior to predictions based on FC (0.59 accuracy, 0.61 AUC). Interpreting model predictions based on SHAP (SHapley Additive exPlanations) values suggested that the most predictive connections were widely distributed and not confined to specific networks. Overall, our analyses suggest (i) ways of improving future fMRI-based generative embedding approaches for the early detection of individuals at-risk for depression and that (ii) achieving accuracies of clinical utility may require combination of fMRI with other data modalities.

Transcriptional substrates of brain structural and functional impairments in drug-naive first-episode patients with major depressive disorder

BACKGROUND

Despite remarkable success in identifying genetic risk factors for depression, there are still open questions about the exact genetic mechanisms underlying certain disease phenotypes, such as brain structural and functional impairments.

METHODS

Comprehensive multi-modal neuroimaging meta-analyses were conducted to examine changes in brain structure and function in drug-naive first-episode patients with major depressive disorder (DF-MDD). Combined with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were performed to identify genes whose expression related to these brain structural and functional changes, followed by a range of gene functional signature analyses.

RESULTS

Meta-analyses revealed gray matter atrophy in the insula, temporal pole, cerebellum and postcentral gyrus, and a complex pattern of hyper-function in the temporal pole and hypo-function in the cuneus/precuneus, angular gyrus and lingual gyrus in DF-MDD. Moreover, these brain structural and functional changes were spatially associated with the expression of 1194 and 1733 genes, respectively. Importantly, there were commonalities and differences in the two gene sets and their functional signatures including functional enrichment, specific expression, behavioral relevance, and constructed protein-protein interaction networks.

LIMITATIONS

The results merit further verification using a large sample of DF-MDD.

CONCLUSIONS

Our findings not only corroborate the polygenic nature of depression, but also suggest common and distinct genetic modulations of brain structural and functional impairments in this disorder.

Disentangling the relationship between depression and chronic widespread pain: A Mendelian randomisation study

OBJECTIVE

Depression and chronic widespread pain (CWP) frequently coexist, but whether depression is an independent causal risk factor for CWP, and/or vice versa, remains unclear. We investigated the bidirectional causal relationship between depression and CWP.

METHODS

We performed a two-sample Mendelian randomisation (MR) study to estimate the causal relationship between genetically predicted depression (170,756 cases, 329,443 controls) and risk of CWP (6,914 cases, 242,929 controls), and the effect of CWP on depression susceptibility, using large population-level genetic data. We used a new MR method, Causal Analysis Using Summary Effect estimates (CAUSE), which allows for sample overlap, in addition to traditional MR and sensitivity analyses.

RESULTS

For each doubling in odds of genetic liability to depression, the risk of chronic widespread pain was increased (OR 1.004, 95% credible interval 1.003-1.005; p = 7.3 × 10^-5 that the causal model is a better fit than non-causal model). There was bidirectional evidence of causality, with genetic liability to chronic widespread pain increasing depression susceptibility (OR 2.31; 95%CrI 1.57, 3.40; p = 0.0026 that the causal model is a better fit). Other MR methods produced concordant results.

CONCLUSIONS

This study provides evidence in support of a bidirectional causal relationship between depression and increased risk of chronic widespread pain, whilst overcoming the major limitations of previous epidemiological studies. Interventions for depression may be an effective strategy to prevent or reduce the burden of chronic widespread pain and vice versa.

Multi-ancestry phenome-wide association of complement component 4 variation with psychiatric and brain phenotypes in youth

BACKGROUND

Increased expression of the complement component 4A (C4A) gene is associated with a greater lifetime risk of schizophrenia. In the brain, C4A is involved in synaptic pruning; yet, it remains unclear the extent to which upregulation of C4A alters brain development or is associated with the risk for psychotic symptoms in childhood. Here, we perform a multi-ancestry phenome-wide association study in 7789 children aged 9-12 years to examine the relationship between genetically regulated expression (GREx) of C4A, childhood brain structure, cognition, and psychiatric symptoms.

RESULTS

While C4A GREx is not related to childhood psychotic experiences, cognition, or global measures of brain structure, it is associated with a localized reduction in regional surface area (SA) of the entorhinal cortex. Furthermore, we show that reduced entorhinal cortex SA at 9-10 years predicts a greater number and severity of psychosis-like events at 1-year and 2-year follow-up time points. We also demonstrate that the effects of C4A on the entorhinal cortex are independent of genome-wide polygenic risk for schizophrenia.

CONCLUSIONS

Our results suggest neurodevelopmental effects of C4A on childhood medial temporal lobe structure, which may serve as a biomarker for schizophrenia risk prior to symptom onset.

A bioinformatics approach to identifying the biomarkers and pathogenesis of major depressive disorder combined with acute myocardial infarction

This study investigated the pathogenesis of major depressive disorder (MDD) and acute myocardial infarction (AMI) using bioinformatics. We analyzed MDD and AMI (MDD-AMI) datasets provided by the Gene Expression Omnibus (GEO) database for genes common to MDD and AMI using GEO2R and weighted gene co-expression network analysis (WGCNA). We also performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and we used Disease Ontology (DO) analysis to identify a) the pathways through which genes function and b) comorbidities. We also created a protein-protein interaction (PPI) network using the STRING database to identify the hub genes and biomarkers. NetworkAnalyst 3.0 was used to construct a transcription factor (TF) gene regulatory network. We also identified relevant complications and potential drug candidates. The 27 genes common to MDD and AMI were enriched in the pathways regulating TFs and mediating immunity and inflammation. The hub genes in the PPI network included TLR2, HP, ICAM1, LCN2, LTF, VCAN, S100A9 and NFKBIA. Key TFs were KLF9, KLF11, ZNF24, and ZNF580. Cardiovascular, pancreatic, and skeletal diseases were common complications. Hydrocortisone, simvastatin, and estradiol were candidate treatment drugs. Identification of these genes and their pathways may provide new targets for further research on the pathogenesis, biomarkers, and treatment of MDD-AMI. Together our results suggested that TLR2 and VCAN might be the key genes associated with MDD complicated by AMI.

Identification of novel targets and pathways to distinguish suicide dependent or independent on depression diagnosis

In recent years, postmortem brain studies have revealed that some molecular, cellular, and circuit changes associated with suicide, have an independent or additive effect on depression. The aim of the present study is to identify potential phenotypic, tissue, and sex-specific novel targets and pathways to distinguish depression or suicide from major depressive disorder (MDD) comorbid with suicide. The mRNA expression profiling datasets from two previous independent postmortem brain studies of suicide and depression (GSE102556 and GSE101521) were retrieved from the GEO database. Machine learning analysis was used to differentiate three regrouped gene expression profiles, i.e., MDD with suicide, MDD without suicide, and suicide without depression. Weighted correlation network analysis (WGCNA) was further conducted to identify the key modules and hub genes significantly associated with each of these three sub-phenotypes. TissueEnrich approaches were used to find the essential brain tissues and the difference of tissue enriched genes between depression with or without suicide. Dysregulated gene expression cross two variables, including phenotypes and tissues, were determined by global analysis with Vegan. RRHO analysis was applied to examine the difference in global expression pattern between male and female groups. Using the optimized machine learning model, several ncRNAs and mRNAs with higher AUC and MeanDecreaseGini, including GCNT1P1 and AC092745.1, etc., were identified as potential molecular targets to distinguish suicide with, or without MDD and depression without suicide. WGCNA analysis identified some key modules significantly associated with these three phenotypes, and the gene biological functions of the key modules mainly relate to ncRNA and miRNA processing, as well as oxidoreductase and dehydrogenase activity. Hub genes such as RP11-349A22.5, C20orf196, MAPK8IP3 and RP11-697N18.2 were found in these key modules. TissueEnrich analysis showed that nucleus accumbens and subiculum were significantly changed among the 6 brain regions studied. Global analysis with Vegan and RRHO identified PRS26, ARNT and SYN3 as the most significantly differentially expressed genes across phenotype and tissues, and there was little overlap between the male and female groups. In this study, we have identified novel gene targets, as well as annotated functions of co-expression patterns and hub genes that are significantly distinctive between depression with suicide, depression without suicide, and suicide without depression. Moreover, global analysis across three phenotypes and tissues confirmed the evidence of sex difference in mood disorders.

Genomic patterns linked to gray matter alterations underlying working memory deficits in adults and adolescents with attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder, with onset in childhood and a considerable likelihood to persist into adulthood. Our previous work has identified that across adults and adolescents with ADHD, gray matter volume (GMV) alteration in the frontal cortex was consistently associated with working memory underperformance, and GMV alteration in the cerebellum was associated with inattention. Recent knowledge regarding ADHD genetic risk loci makes it feasible to investigate genomic factors underlying these persistent GMV alterations, potentially illuminating the pathology of ADHD persistence. Based on this, we applied a sparsity-constrained multivariate data fusion approach, sparse parallel independent component analysis, to GMV variations in the frontal and cerebellum regions and candidate risk single nucleotide polymorphisms (SNPs) data from 341 unrelated adult participants, including 167 individuals with ADHD, 47 unaffected siblings, and 127 healthy controls. We identified one SNP component significantly associated with one GMV component in superior/middle frontal regions and replicated this association in 317 adolescents from ADHD families. The association was stronger in individuals with ADHD than in controls, and stronger in adults and older adolescents than in younger ones. The SNP component highlights 93 SNPs in long non-coding RNAs mainly in chromosome 5 and 21 protein-coding genes that are significantly enriched in human neuron cells. Eighteen identified SNPs have regulation effects on gene expression, transcript expression, isoform percentage, or methylation level in frontal regions. Identified genes highlight MEF2C, CADM2, and CADPS2, which are relevant for modulating neuronal substrates underlying high-level cognition in ADHD, and their causality effects on ADHD persistence await further investigations. Overall, through a multivariate analysis, we have revealed a genomic pattern underpinning the frontal gray matter variation related to working memory deficit in ADHD.

Association between sleep duration and metabolic syndrome: linear and nonlinear Mendelian randomization analyses

BACKGROUND

Observational studies have found that both short and long sleep duration are associated with increased risk of metabolic syndrome (MetS). This study aimed to examine the associations of genetically determined sleep durations with MetS and its five components (i.e., central obesity, high blood pressure, dyslipidemia, hypertriglyceridemia, and hyperglycemia) among a group of elderly population.

METHODS

In 335,727 participants of White British from the UK Biobank, linear Mendelian randomization (MR) methods were first employed to examine the causal association of genetically predicted continuous sleep duration with MetS and its each component. Nonlinear MR analyses were performed to determine the nonlinearity of these associations. The causal associations of short and long sleep duration with MetS and its components were further assessed by using genetic variants that associated with short (≤ 6 h) and long sleep (≥ 9 h) durations.

RESULTS

Linear MR analyses demonstrated that genetically predicted 1-h longer sleep duration was associated with a 13% lower risk of MetS, a 30% lower risk of central obesity, and a 26% lower risk of hyperglycemia. Non-linear MR analyses provided evidence for non-linear associations of genetically predicted sleep duration with MetS and its five components (all P values < 0.008). Genetically predicted short sleep duration was moderately associated with MetS and its four components, including central obesity, dyslipidemia, hypertriglyceridemia, and hyperglycemia (all P values < 0.002), whereas genetically long sleep duration was not associated with MetS and any of its components.

CONCLUSIONS

Genetically predicted short sleep duration, but not genetically predicted long sleep duration, is a potentially causal risk factor for MetS.

The Role of Genetics in the Development and Pharmacotherapy of Depression and Its Impact on Drug Discovery

Complex disorders, such as depression, remain a mystery for scientists. Although genetic factors are considered important for the prediction of one's vulnerability, it is hard to estimate the exact risk for a patient to develop depression, based only on one category of vulnerability criteria. Genetic factors also regulate drug metabolism, and when they are identified in a specific combination, may result in increased drug resistance. A proper understanding of the genetic basis of depression assists in the development of novel promising medications and effective disorder management schemes. This review aims to analyze the recent literature focusing on the correlation between specific genes and the occurrence of depression. Moreover, certain aspects targeting a high drug resistance identified among patients suffering from major depressive disorder were highlighted in this manuscript. An expected direction of future drug discovery campaigns was also discussed.

Genome-wide association studies on Northern Italy isolated populations provide further support concerning genetic susceptibility for major depressive disorder

OBJECTIVES

Major depressive disorder (MDD) is a psychiatric disorder with pathogenesis influenced by both genetic and environmental factors. To date, the molecular-level understanding of its aetiology remains unclear. Thus, we aimed to identify genetic variants and susceptibility genes for MDD with a genome-wide association study (GWAS) approach.

METHODS

We performed a meta-analysis of GWASs and a gene-based analysis on two Northern Italy isolated populations (cases/controls n = 166/472 and 33/320), followed by replication and polygenic risk score (PRS) analyses in Italian independent samples (cases n = 464, controls n = 339).

RESULTS

We identified two novel MDD-associated genes, KCNQ5 (lead SNP rs867262, p = 3.82 × 10^-9) and CTNNA2 (rs6729523, p = 1.25 × 10^-8). The gene-based analysis revealed another six genes (p < 2.703 × 10^-6): GRM7, CTNT4, SNRK, SRGAP3, TRAPPC9, and FHIT. No replication of the genome-wide significant SNPs was found in the independent cohort, even if 14 SNPs around CTNNA2 showed association with MDD and related phenotypes at the nominal level of p (<0.05). Furthermore, the PRS model developed in the discovery cohort discriminated cases and controls in the replication cohort.

CONCLUSIONS

Our work suggests new possible genes associated with MDD, and the PRS analysis confirms the polygenic nature of this disorder. Future studies are required to better understand the role of these findings in MDD.

Causal association of juvenile idiopathic arthritis-associated uveitis with depression and anxiety: a bidirectional Mendelian randomization study

PURPOSE

The objective of this article was to examine the potential effect of juvenile idiopathic arthritis-associated uveitis (JIAU) on the risk of major depressive and anxiety disorders through Mendelian randomization (MR) study.

METHODS

Genetic instrumental variables from the largest available genome-wide association study for JIAU, major depressive disorder, and anxiety disorder were applied. A set of complementary MR approaches including inverse-variance weighted (IVW) were carried out to verify the estimate association and assess horizontal pleiotropy.

RESULTS

Our results indicated that genetically driven JIAU did not causally produce changes in major depressive or anxiety disorders (IVW: OR = 1.001, 95% CI = 0.997-1.006, P = 0.581; IVW: OR = 1.006, 95% CI = 0.980-1.033, P = 0.649, respectively). In addition, the risk of JIAU could not be influenced by genetically predicted major depressive or anxiety disorders (IVW: OR = 1.132, 95% CI = 0.914-1.404, P = 0.256; IVW: OR = 1.019, 95% CI = 0.548-1.896, P = 0.953, respectively). Besides, several sensitivity analyses indicated that our MR results were robust and no horizontal pleiotropy was observed (P > 0.05).

CONCLUSIONS

Our MR study does not reveal sufficient evidence to support the causal association of JIAU with the development of major depressive or anxiety disorders in both directions. Further large studies are warranted to validate the undetermined relationship between JIAU and the risk of major depressive or anxiety disorders.

Assessment of Bidirectional Relationships between Mental Illness and Rheumatoid Arthritis: A Two-Sample Mendelian Randomization Study

A correlation between mental illness and systemic rheumatoid arthritis (RA) has been observed in several prior investigations. However, little is known about the causative relationship between them. The present study aimed to systematically investigate the potential association between genetically determined mental illness and RA. Two-sample bidirectional Mendelian randomization (MR) analysis was performed using publicly released genome-wide association studies (GWAS). We selected independent genetic variants associated with four mental illnesses (bipolar disorder, broad depression, major depression, and anxiety) as instrumental variables. The inverse variance weighted (IVW) method was used as the primary analysis to assess the causal relationship between mental illness and RA. Results of the IVW analysis suggested that genetic predisposition to bipolar disorder was associated with a decreased risk of RA (odds ratio [OR] = 0.825, 95% CI = 0.716 to 0.95, p = 0.007). Furthermore, we did not find a significant causal effect of RA on bipolar disorder in the reverse MR analysis (p > 0.05). In addition, our study found no evidence of a bidirectional causal relationship between genetically predicted broad depression, major depression, anxiety, and RA (p > 0.05). The genetically proxied bipolar disorder population has a lower RA risk, which may indicate that there is a hidden mechanism for inhibiting the pathogenesis of RA in bipolar disorder. However, results do not support a causal connection between depression, anxiety, and RA.

Exploring the overlap between alopecia areata and major depressive disorder: Epidemiological and genetic perspectives

BACKGROUND

Research suggests that Alopecia areata (AA) and Major Depressive Disorder (MDD) show substantial comorbidity. To date, no study has investigated the hypothesis that this is attributable to shared genetic aetiology.

OBJECTIVES

To investigate AA-MDD comorbidity on the epidemiological and molecular genetic levels.

METHODS

First, epidemiological analyses were performed using data from a cohort of adult German health insurance beneficiaries (n = 1.855 million) to determine the population-based prevalence of AA-MDD comorbidity. Second, analyses were performed to determine the prevalence of MDD in a clinical AA case-control sample with data on psychiatric phenotypes, stratifying for demographic factors to identify possible contributing factors to AA-MDD comorbidity. Third, the genetic overlap between AA and MDD was investigated using a polygenic risk score (PRS) approach and linkage disequilibrium score (LDSC) regression. For PRS, summary statistics from a large MDD GWAS meta-analysis (PGC-MD2) were used as the training sample, while a Central European AA cohort, including the above-mentioned AA patients, and an independent replication US-AA cohort were used as target samples. LDSC was performed using summary statistics of PGC-MD2 and the largest AA meta-analysis to date.

RESULTS

High levels of AA-MDD comorbidity were reported in the population-based (MDD in 24% of AA patients), and clinical samples (MDD in 44% of AA patients). MDD-PRS explained a modest proportion of variance in AA case-control status (R²  = 1%). This signal was limited to the major histocompatibility complex (MHC) region on chromosome 6. LDSC regression (excluding MHC) revealed no significant genetic correlation between AA and MDD.

CONCLUSIONS

As in previous research, AA patients showed an increased prevalence of MDD. The present analyses suggest that genetic overlap may be confined to the MHC region, which is implicated in immune function. More detailed investigation is required to refine understanding of how the MHC is involved in the development of AA and MDD comorbidity.

Cerebral blood flow changes and their genetic mechanisms in major depressive disorder: a combined neuroimaging and transcriptome study

BACKGROUND

Extensive research has shown abnormal cerebral blood flow (CBF) in patients with major depressive disorder (MDD) that is a heritable disease. The objective of this study was to investigate the genetic mechanisms of CBF abnormalities in MDD.

METHODS

To achieve a more thorough characterization of CBF changes in MDD, we performed a comprehensive neuroimaging meta-analysis of previous literature as well as examined group CBF differences in an independent sample of 133 MDD patients and 133 controls. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were conducted to identify genes whose expression correlated with CBF changes in MDD, followed by a set of gene functional feature analyses.

RESULTS

We found increased CBF in the reward circuitry and default-mode network and decreased CBF in the visual system in MDD patients. Moreover, these CBF changes were spatially associated with expression of 1532 genes, which were enriched for important molecular functions, biological processes, and cellular components of the cerebral cortex as well as several common mental disorders. Concurrently, these genes were specifically expressed in the brain tissue, in immune cells and neurons, and during nearly all developmental stages. Regarding behavioral relevance, these genes were associated with domains involving emotion and sensation. In addition, these genes could construct a protein-protein interaction network supported by 60 putative hub genes with functional significance.

CONCLUSIONS

Our findings suggest a cerebral perfusion redistribution in MDD, which may be a consequence of complex interactions of a wide range of genes with diverse functional features.

Methylation in MAD1L1 is associated with the severity of suicide attempt and phenotypes of depression

Depression is a multifactorial disorder representing a significant public health burden. Previous studies have linked multiple single nucleotide polymorphisms with depressive phenotypes and suicidal behavior. MAD1L1 is a mitosis metaphase checkpoint protein that has been linked to depression in GWAS. Using a longitudinal EWAS approach in an adolescent cohort at two time points (n = 216 and n = 154), we identified differentially methylated sites that were associated with depression-related genetic variants in MAD1L1. Three methylation loci (cg02825527, cg18302629, and cg19624444) were consistently hypomethylated in the minor allele carriers, being cross-dependent on several SNPs. We further investigated whether DNA methylation at these CpGs is associated with depressive psychiatric phenotypes in independent cohorts. The first site (cg02825527) was hypomethylated in blood (exp(β) = 84.521, p value ~ 0.003) in participants with severe suicide attempts (n = 88). The same locus showed increased methylation in glial cells (exp(β) = 0.041, p value ~ 0.004) in the validation cohort, involving 29 depressed patients and 29 controls, and showed a trend for association with suicide (n = 40, p value ~ 0.089) and trend for association with depression treatment (n = 377, p value ~ 0.075). The second CpG (cg18302629) was significantly hypomethylated in depressed participants (exp(β) = 56.374, p value ~ 0.023) in glial cells, but did not show associations in the discovery cohorts. The last methylation site (cg19624444) was hypomethylated in the whole blood of severe suicide attempters; however, this association was at the borderline for statistical significance (p value ~ 0.061). This locus, however, showed a strong association with depression treatment in the validation cohort (exp(β) = 2.237, p value ~ 0.003) with 377 participants. The direction of associations between psychiatric phenotypes appeared to be different in the whole blood in comparison with brain samples for cg02825527 and cg19624444. The association analysis between methylation at cg18302629 and cg19624444 and MAD1L1 transcript levels in CD¹⁴⁺ cells shows a potential link between methylation at these CpGs and MAD1L1 expression. This study suggests evidence that methylation at MAD1L1 is important for psychiatric health as supported by several independent cohorts.

GWAS of depression in 4,520 individuals from the Russian population highlights the role of MAGI2 (S-SCAM) in the gut-brain axis

We present the results of the depression Genome-wide association studies study performed on a cohort of Russian-descent individuals, which identified a novel association at chromosome 7q21 locus. Gene prioritization analysis based on already known depression risk genes indicated MAGI2 (S-SCAM) as the most probable gene from the locus and potential susceptibility gene for the disease. Brain and gut expression patterns were the main features highlighting functional relatedness of MAGI2 to the previously known depression risk genes. Local genetic covariance analysis, analysis of gene expression, provided initial suggestive evidence of hospital anxiety and depression scale and diagnostic and statistical manual of mental disorders scales having a different relationship with gut-brain axis disturbance. It should be noted, that while several independent methods successfully in silico validate the role of MAGI2, we were unable to replicate genetic association for the leading variant in the MAGI2 locus, therefore the role of rs521851 in depression should be interpreted with caution.

Association analyses of the autosomal genome and mitochondrial DNA with accelerometry-derived sleep parameters in depressed UK biobank subjects

BACKGROUND

The bidirectional relationship between sleep disturbances and depression is well documented, yet the biology of sleep is not fully understood. Mitochondria have become of interest not only because of the connection between sleep and metabolism but also because of mitochondria's involvement in the production of reactive oxygen species, which are largely scavenged during sleep.

METHODS

Genome-wide association studies (GWAS) of eight accelerometry-derived sleep measures were performed across both the autosomal and mitochondrial DNA (mtDNA) among two severity levels of depression in UK Biobank participants. We calculated SNP heritability for each of the sleep measures. Linear regression was performed to test associations and mitochondrial haplogroups.

RESULTS

Variants included in the GWAS accounted for moderate heritability of bedtime (19.6%, p = 4.75 × 10^-7), sleep duration (16.6%, p = 8.58 × 10^-6) and duration of longest sleep bout (22.6%, p = 4.64 × 10^-4). No variants passed genome-wide significance in the autosomal genome. The top hit in the severe depression sample was rs145019802, near GOLGA8B, for sleep efficiency (p = 1.17 × 10^-7), and the top hit in the broad depression sample was rs7100859, an intergenic SNP, and nap duration (p = 1.25 × 10^-7). Top mtDNA loci were m.12633C > A of MT-ND5 with bedtime (p = 0.002) in the severe sample and m.16186C > T of the control region with nap duration (p = 0.002) in the broad sample.

CONCLUSION

SNP heritability estimates support the involvement of common SNPs in specific sleep measures among depressed individuals. This is the first study to analyze mtDNA variance in sleep measures in depressed individuals. Our mtDNA findings, although nominally significant, provide preliminary suggestion that mitochondria are involved in sleep.

Mendelian randomization analysis does not reveal a causal influence of mental diseases on osteoporosis

Introduction

Osteoporosis (OP) is primarily diagnosed through bone mineral density (BMD) measurements, and it often leads to fracture. Observational studies suggest that several mental diseases (MDs) may be linked to OP, but the causal direction of these associations remain unclear. This study aims to explore the potential causal association between five MDs (Schizophrenia, Depression, Alzheimer's disease, Parkinson's disease, and Epilepsy) and the risk of OP.

Methods

First, single-nucleotide polymorphisms (SNPs) were filtered from summary-level genome-wide association studies using quality control measures. Subsequently, we employed two-sample Mendelian randomization (MR) analysis to indirectly analyze the causal effect of MDs on the risk of OP through bone mineral density (in total body, femoral neck, lumbar spine, forearm, and heel) and fractures (in leg, arm, heel, spine, and osteoporotic fractures). Lastly, the causal effect of the MDs on the risk of OP was evaluated directly through OP. MR analysis was performed using several methods, including inverse variance weighting (IVW)-random effects, IVW-fixed effects, maximum likelihood, weighted median, MR-Egger regression, and penalized weighted median.

Results

The results did not show any evidence of a causal relationship between MDs and the risk of OP (with almost all P values > 0.05). The robustness of the above results was proved to be good.

Discussion

In conclusion, this study did not find evidence supporting the claim that MDs have a definitive impact on the risk of OP, which contradicts many existing observational reports. Further studies are needed to determine the potential mechanisms of the associations observed in observational studies.

Symptom dimensions of major depression in a large community-based cohort

BACKGROUND

Our understanding of major depression is complicated by substantial heterogeneity in disease presentation, which can be disentangled by data-driven analyses of depressive symptom dimensions. We aimed to determine the clinical portrait of such symptom dimensions among individuals in the community.

METHODS

This cross-sectional study consisted of 25 261 self-reported White UK Biobank participants with major depression. Nine questions from the UK Biobank Mental Health Questionnaire encompassing depressive symptoms were decomposed into underlying factors or 'symptom dimensions' via factor analysis, which were then tested for association with psychiatric diagnoses and polygenic risk scores for major depressive disorder (MDD), bipolar disorder and schizophrenia. Replication was performed among 655 self-reported non-White participants, across sexes, and among 7190 individuals with an ICD-10 code for MDD from linked inpatient or primary care records.

RESULTS

Four broad symptom dimensions were identified, encompassing negative cognition, functional impairment, insomnia and atypical symptoms. These dimensions replicated across ancestries, sexes and individuals with inpatient or primary care MDD diagnoses, and were also consistent among 43 090 self-reported White participants with undiagnosed self-reported depression. Every dimension was associated with increased risk of nearly every psychiatric diagnosis and polygenic risk score. However, while certain psychiatric diagnoses were disproportionately associated with specific symptom dimensions, the three polygenic risk scores did not show the same specificity of associations.

CONCLUSIONS

An analysis of questionnaire data from a large community-based cohort reveals four replicable symptom dimensions of depression with distinct clinical, but not genetic, correlates.

Causal associations between major depressive disorder and COVID-19

Background

We aimed to evaluate whether major depressive disorder (MDD) could aggravate the outcomes of coronavirus disease 2019 (COVID-19) or whether the genetic liability to COVID-19 could trigger MDD.

Aims

We aimed to assess bidirectional causal associations between MDD and COVID-19.

Methods

We performed genetic correlation and Mendelian randomisation (MR) analyses to assess potential associations between MDD and three COVID-19 outcomes. Literature-based network analysis was conducted to construct molecular pathways connecting MDD and COVID-19.

Results

We found that MDD has positive genetic correlations with COVID-19 outcomes (r_g: 0.10-0.15). Our MR analysis indicated that genetic liability to MDD is associated with increased risks of COVID-19 infection (odds ratio (OR)=1.05, 95% confidence interval (CI): 1.00 to 1.10, p=0.039). However, genetic liability to the three COVID-19 outcomes did not confer any causal effects on MDD. Pathway analysis identified a panel of immunity-related genes that may mediate the links between MDD and COVID-19.

Conclusions

Our study suggests that MDD may increase the susceptibility to COVID-19. Our findings emphasise the need to increase social support and improve mental health intervention networks for people with mood disorders during the pandemic.

Passive and active suicidal ideation in a population-based sample of older adults: Associations with polygenic risk scores of relevance for suicidal behavior

INTRODUCTION

There are few studies investigating genetic factors related to suicidal ideation or behavior in older adult populations. Our aim was to test associations between passive and active suicidal ideation and polygenic risk scores (PRSs) for suicidality and other traits of relevance for suicidality in old age (i.e. depression, neuroticism, loneliness, Alzheimer's disease, cognitive performance, educational attainment, and several specified vascular diseases) in a population-based sample aged 70 years and older.

METHODS

Participants in the prospective H70 study in Gothenburg, Sweden, took part in a psychiatric examination that included the Paykel questions on active and passive suicidal ideation. Genotyping was performed with the Neurochip (Illumina). After quality control of the genetic data the sample included 3467 participants. PRSs for suicidality and other related traits were calculated based on summary statistics from recent GWASs of relevance. Exclusion of persons with dementia or incomplete data on suicidal ideation yielded 3019 participants, age range 70-101 years. Associations between past year suicidal ideation (any level) and selected PRSs were analysed using general estimation equation (GEE) models, adjusted for sex and age.

RESULTS

We observed associations between passive/active suicidal ideation and PRSs for depression (three versions), neuroticism, and general cognitive performance. After excluding individuals with current major depressive disorder (MDD), similar associations were seen with PRS for neuroticism, general cognitive performance and two PRSs for depression. No associations were found between suicidal ideation and PRSs for suicidality, loneliness, Alzheimer's disease, educational attainment, or vascular disease.

DISCUSSION

Our results could indicate which types of genetic susceptibility that are of importance for suicidality in old age, and these findings can help to shed light on potential mechanisms that may be involved in passive and active suicidal ideation in late-life, also in those with no current MDD. However, due to the limited sample size, the results need to be interpreted with caution until replicated in larger samples.

Depression-Associated Negr1 Gene-Deficiency Induces Alterations in the Monoaminergic Neurotransmission Enhancing Time-Dependent Sensitization to Amphetamine in Male Mice

In GWAS studies, the neural adhesion molecule encoding the neuronal growth regulator 1 (NEGR1) gene has been consistently linked with both depression and obesity. Although the linkage between NEGR1 and depression is the strongest, evidence also suggests the involvement of NEGR1 in a wide spectrum of psychiatric conditions. Here we show the expression of NEGR1 both in tyrosine- and tryptophan hydroxylase-positive cells. Negr1-/- mice show a time-dependent increase in behavioral sensitization to amphetamine associated with increased dopamine release in both the dorsal and ventral striatum. Upregulation of transcripts encoding dopamine and serotonin transporters and higher levels of several monoamines and their metabolites was evident in distinct brain areas of Negr1-/- mice. Chronic (23 days) escitalopram-induced reduction of serotonin and dopamine turnover is enhanced in Negr1-/- mice, and escitalopram rescued reduced weight of hippocampi in Negr1-/- mice. The current study is the first to show alterations in the brain monoaminergic systems in Negr1-deficient mice, suggesting that monoaminergic neural circuits contribute to both depressive and obesity-related phenotypes linked to the human NEGR1 gene.

Patient characteristics associated with retrospectively self-reported treatment outcomes following psychological therapy for anxiety or depressive disorders - a cohort of GLAD study participants

BACKGROUND

Progress towards stratified care for anxiety and depression will require the identification of new predictors. We collected data on retrospectively self-reported therapeutic outcomes in adults who received psychological therapy in the UK in the past ten years. We aimed to replicate factors associated with traditional treatment outcome measures from the literature.

METHODS

Participants were from the Genetic Links to Anxiety and Depression (GLAD) Study, a UK-based volunteer cohort study. We investigated associations between retrospectively self-reported outcomes following therapy, on a five-point scale (global rating of change; GRC) and a range of sociodemographic, clinical and therapy-related factors, using ordinal logistic regression models (n = 2890).

RESULTS

Four factors were associated with therapy outcomes (adjusted odds ratios, OR). One sociodemographic factor, having university-level education, was associated with favourable outcomes (OR = 1.37, 95%CI: 1.18, 1.59). Two clinical factors, greater number of reported episodes of illness (OR = 0.95, 95%CI: 0.92, 0.97) and higher levels of personality disorder symptoms (OR = 0.89, 95%CI: 0.87, 0.91), were associated with less favourable outcomes. Finally, reported regular use of additional therapeutic activities was associated with favourable outcomes (OR = 1.39, 95%CI: 1.19, 1.63). There were no statistically significant differences between fully adjusted multivariable and unadjusted univariable odds ratios.

CONCLUSION

Therapy outcome data can be collected quickly and inexpensively using retrospectively self-reported measures in large observational cohorts. Retrospectively self-reported therapy outcomes were associated with four factors previously reported in the literature. Similar data collected in larger observational cohorts may enable detection of novel associations with therapy outcomes, to generate new hypotheses, which can be followed up in prospective studies.

Meta-analysis of epigenome-wide association studies of major depressive disorder

Epigenetic mechanisms have been hypothesized to play a role in the etiology of major depressive disorder (MDD). In this study, we performed a meta-analysis between two case-control MDD cohorts to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) in MDD. Using samples from two Cohorts (a total of 298 MDD cases and 63 controls with repeated samples, on average ~ 1.8 samples/subject), we performed an EWAS meta-analysis. Multiple cytosine-phosphate-guanine sites annotated to TNNT3 were associated with MDD reaching study-wide significance, including cg08337959 (p = 2.3 × 10^-11). Among DMPs with association p values less than 0.0001, pathways from REACTOME such as Ras activation upon Ca²⁺ influx through the NMDA receptor (p = 0.0001, p-adjusted = 0.05) and long-term potentiation (p = 0.0002, p-adjusted = 0.05) were enriched in this study. A total of 127 DMRs with Sidak-corrected p value < 0.05 were identified from the meta-analysis, including DMRs annotated to TNNT3 (chr11: 1948933 to 1949130 [6 probes], Sidak corrected P value = 4.32 × 10^-41), S100A13 (chr1: 153599479 to 153600972 [22 probes], Sidak corrected P value = 5.32 × 10^-18), NRXN1 (chr2: 50201413 to 50201505 [4 probes], Sidak corrected P value = 1.19 × 10^-11), IL17RA (chr22: 17564750 to 17565149, Sidak corrected P value = 9.31 × 10^-8), and NPFFR2 (chr4: 72897565 to 72898212, Sidak corrected P value = 8.19 × 10^-7). Using 2 Cohorts of depression case-control samples, we identified DMPs and DMRs associated with MDD. The molecular pathways implicated by these data include mechanisms involved in neuronal synaptic plasticity, calcium signaling, and inflammation, consistent with reports from previous genetic and protein biomarker studies indicating that these mechanisms are involved in the neurobiology of depression.

Genetic similarities and differences among distinct definitions of depression

Depression is a common and complex psychiatric illness with considerable heritability. Genome-wide association studies (GWAS) have been conducted among different definitions of depression based on different diagnostic criteria. However, the heritability explained by different depression GWAS and the identified loci varied widely. To understand the genetic architectures of different definitions of depression, we conducted a series of genetic analyses including linkage disequilibrium score regression (LDSC), Mendelian randomization, and polygenic overlap quantification and identification. Different definitions of depression and other common psychiatric traits were included in this analysis. We found that although genetic correlations between different definitions of depression were relatively high, they showed substantially different genetic correlation and causality with other psychiatric traits. Using bivariate causal mixture mode (MiXeR) and conjunctional false discovery rate (conjFDR) approach, we observed both shared and unique risk loci across different definitions of depression. Further functional mapping with expression quantitative trait loci (eQTL) information from multiple brain tissues and single cell types indicated distinct genes underlying different definitions of depression, and pathways associated with synapses were significantly enriched in the illness. Our study showed that the genetic architectures of different definitions of depression were distinct and genetic studies of depression should be conducted more cautious.

Leveraging Large-Scale Genetics of PTSD and Cardiovascular Disease to Demonstrate Robust Shared Risk and Improve Risk Prediction Accuracy

OBJECTIVE

Individuals with posttraumatic stress disorder (PTSD) are significantly more likely to be diagnosed with cardiovascular disease (CVD) (e.g., myocardial infarction, stroke). The evidence for this link is so compelling that the National Institutes of Health convened a working group to determine gaps in the literature, including the need for large-scale genomic studies to identify shared genetic risk. The aim of the present study was to address some of these gaps by utilizing PTSD and CVD genome-wide association study (GWAS) summary statistics in a large biobank sample to determine the shared genetic risk of PTSD and CVD.

METHODS

A large health care biobank data set was used (N=36,412), combined with GWAS summary statistics from publicly available large-scale PTSD and CVD studies. Disease phenotypes (e.g., PTSD) were collected from electronic health records. De-identified genetic data from the biobank were genotyped using Illumina SNP array. Summary statistics data sets were processed with the following quality-control criteria: 1) SNP heritability h2 >0.05, 2) compute z-statistics (z=beta/SE or z=log(OR)/SE), 3) filter nonvariable SNPs (0

RESULTS

Significant genetic correlations were found between PTSD and CVD (rG=0.24, SE=0.06), and Mendelian randomization analyses indicated a potential causal link from PTSD to hypertension (β=0.20, SE=0.04), but not the reverse. PTSD summary statistics significantly predicted PTSD diagnostic status (R2=0.27), and this was significantly improved by incorporating summary statistics from CVD and major depressive disorder (R2=1.30). Further, pathway enrichment analyses indicated that genetic variants involved in shared PTSD-CVD risk included those involved in postsynaptic structure, synapse organization, and interleukin-7-mediated signaling pathways.

CONCLUSIONS

The results from this study suggest that PTSD and CVD may share genetic risk. Further, these results implicate PTSD as a risk factor leading to the development of hypertension and coronary artery disease. Additional research is needed to determine the clinical utility of these findings.

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Key Words

• Cardiovascular Disease
• Depressive Disorders
• Genetics/Genomics
• Major Depressive Disorder
• Posttraumatic Stress Disorder (PTSD)

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MESH Headings

• Humans
• Stress Disorders, Post-Traumatic/epidemiology
• Stress Disorders, Post-Traumatic/genetics
• Genome-Wide Association Study
• Genetic Predisposition to Disease/genetics
• Depressive Disorder, Major
• Cardiovascular Diseases/epidemiology
• Cardiovascular Diseases/genetics
• Polymorphism, Single Nucleotide/genetics
• Hypertension

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Grants

• R21 MH112956 NIMH NIH HHS
• R01 MH094757 NIMH NIH HHS
• K23 MH125920 NIMH NIH HHS
• R01 MH106595 NIMH NIH HHS
• P50 MH115874 NIMH NIH HHS
• U54 MH118919 NIMH NIH HHS

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Affiliation(s)

Antonia V. Seligowski Department of Psychiatry, Harvard Medical School, Boston, MA, USA McLean Hospital, Belmont, MA, USA
Burook Misganaw Department of Psychiatry, Harvard Medical School, Boston, MA, USA McLean Hospital, Belmont, MA, USA
Lucie A. Duffy McLean Hospital, Belmont, MA, USA
Kerry J. Ressler Department of Psychiatry, Harvard Medical School, Boston, MA, USA McLean Hospital, Belmont, MA, USA
Guia Guffanti Department of Psychiatry, Harvard Medical School, Boston, MA, USA McLean Hospital, Belmont, MA, USA

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The Genetic Basis for the Increased Prevalence of Metabolic Syndrome among Post-Traumatic Stress Disorder Patients

Post-traumatic stress disorder (PTSD) is a highly debilitating psychiatric disorder that can be triggered by exposure to extreme trauma. Even if PTSD is primarily a psychiatric condition, it is also characterized by adverse somatic comorbidities. One illness commonly co-occurring with PTSD is Metabolic syndrome (MetS), which is defined by a set of health risk/resilience factors including obesity, elevated blood pressure, lower high-density lipoprotein cholesterol, higher low-density lipoprotein cholesterol, higher triglycerides, higher fasting blood glucose and insulin resistance. Here, phenotypic association between PTSD and components of MetS are tested on a military veteran cohort comprising chronic PTSD presentation (n = 310, 47% cases, 83% male). Consistent with previous observations, we found significant phenotypic correlation between the various components of MetS and PTSD severity scores. To examine if this observed symptom correlations stem from a shared genetic background, we conducted genetic correlation analysis using summary statistics data from large-scale genetic studies. Our results show robust positive genetic correlation between PTSD and MetS (rg[SE] = 0.33 [0.056], p = 4.74E-09), and obesity-related components of MetS (rg = 0.25, SE = 0.05, p = 6.4E-08). Prioritizing genomic regions with larger local genetic correlation implicate three significant loci. Overall, these findings show significant genetic overlap between PTSD and MetS, which may in part account for the markedly increased occurrence of MetS among PTSD patients.

Benchmarking post-GWAS analysis tools in major depression: Challenges and implications

Our knowledge of complex disorders has increased in the last years thanks to the identification of genetic variants (GVs) significantly associated with disease phenotypes by genome-wide association studies (GWAS). However, we do not understand yet how these GVs functionally impact disease pathogenesis or their underlying biological mechanisms. Among the multiple post-GWAS methods available, fine-mapping and colocalization approaches are commonly used to identify causal GVs, meaning those with a biological effect on the trait, and their functional effects. Despite the variety of post-GWAS tools available, there is no guideline for method eligibility or validity, even though these methods work under different assumptions when accounting for linkage disequilibrium and integrating molecular annotation data. Moreover, there is no benchmarking of the available tools. In this context, we have applied two different fine-mapping and colocalization methods to the same GWAS on major depression (MD) and expression quantitative trait loci (eQTL) datasets. Our goal is to perform a systematic comparison of the results obtained by the different tools. To that end, we have evaluated their results at different levels: fine-mapped and colocalizing GVs, their target genes and tissue specificity according to gene expression information, as well as the biological processes in which they are involved. Our findings highlight the importance of fine-mapping as a key step for subsequent analysis. Notably, the colocalizing variants, altered genes and targeted tissues differed between methods, even regarding their biological implications. This contribution illustrates an important issue in post-GWAS analysis with relevant consequences on the use of GWAS results for elucidation of disease pathobiology, drug target prioritization and biomarker discovery.

Joint exposure to positive affect, life satisfaction, broad depression, and neuroticism and risk of cardiovascular diseases: A prospective cohort study

BACKGROUND AND AIMS

Psychologic wellbeing can impact cardiovascular health. We aimed to evaluate the joint association of multiple psychologic wellbeing factors with cardiovascular diseases (CVD) and examine whether this association was modified by genetic susceptibility.

METHODS

In the UK Biobank, 126,255 participants free of CVD (coronary heart disease [CHD], stroke, and heart failure [HF]) at baseline, who completed a questionnaire on psychological factors, were included. The psychological wellbeing score was calculated by four factors: happiness, life satisfaction, broad depression, and neuroticism. Cox proportional hazard models were used to assess the association between the psychological wellbeing score and CVD risk.

RESULTS

During the median follow-up of 11.5 years, 10,815 participants had newly diagnosed CVDs. Low life satisfaction, the presence of depression, and neuroticism score ≥1 were significantly associated with an increased risk of CVD in the multivariable-adjusted model. Through decreasing the psychological wellbeing score, there were significant increasing linear trends in the risk of CVD, CHD, stroke, and HF (all p for trend < 0.001). Participants with the lowest psychological wellbeing score had the highest risk for CVD (HR 1.51, 95% CI 1.42-1.61). Women were more susceptible to worse psychological wellbeing status for CVD than men (p for interaction = 0.009). The associations of the psychological wellbeing score with CVD were consistent across genetic risk (p for interaction >0.05). When considered jointly, participants exposed to high-risk psychological wellbeing and genetic status had a 2.70-fold (95% CI 2.25-3.24) risk for CHD.

CONCLUSIONS

Joint exposure to multiple psychological wellbeing factors was associated with increased risks of incident CVD in an additive manner, regardless of genetic susceptibility.

Regional gene expression signatures are associated with sex-specific functional connectivity changes in depression

The neural substrates of depression may differ in men and women, but the underlying mechanisms are incompletely understood. Here, we show that depression is associated with sex-specific patterns of abnormal functional connectivity in the default mode network and in five regions of interest with sexually dimorphic transcriptional effects. Regional differences in gene expression in two independent datasets explained the neuroanatomical distribution of abnormal connectivity. These gene sets varied by sex and were strongly enriched for genes implicated in depression, synapse function, immune signaling, and neurodevelopment. In an independent sample, we confirmed the prediction that individual differences in default mode network connectivity are explained by inferred brain expression levels for six depression-related genes, including PCDH8, a brain-specific protocadherin integral membrane protein implicated in activity-related synaptic reorganization. Together, our results delineate both shared and sex-specific changes in the organization of depression-related functional networks, with implications for biomarker development and fMRI-guided therapeutic neuromodulation.

Local dynamic spontaneous brain activity changes in first-episode, treatment-naïve patients with major depressive disorder and their associated gene expression profiles

BACKGROUND

Major depressive disorder (MDD) is a common debilitating disorder characterized by impaired spontaneous brain activity, yet little is known about its alterations in dynamic properties and the molecular mechanisms associated with these changes.

METHODS

Based on the resting-state functional MRI data of 65 first-episode, treatment-naïve patients with MDD and 66 healthy controls, we compared dynamic regional homogeneity (dReHo) of spontaneous brain activity between the two groups, and we investigated gene expression profiles associated with dReHo alterations in MDD by leveraging transcriptional data from the Allen Human Brain Atlas and weighted gene co-expression network analysis.

RESULTS

Compared with healthy controls, patients with MDD consistently showed reduced dReHo in both fusiform gyri and in the right temporal pole and hippocampus. The expression profiles of 16 gene modules were correlated with dReHo alterations in MDD. These gene modules were enriched for various biological process terms, including immune, synaptic signalling, ion channels, mitochondrial function and protein metabolism, and were preferentially expressed in different cell types.

CONCLUSIONS

Patients with MDD have reduced dReHo in brain areas associated with emotional and cognitive regulation, and these changes may be related to complex polygenetic and polypathway mechanisms.

Mental Health Symptom Reduction Using Digital Therapeutics Care Informed by Genomic SNPs and Gut Microbiome Signatures

Neuropsychiatric diseases and obesity are major components of morbidity and health care costs, with genetic, lifestyle, and gut microbiome factors linked to their etiology. Dietary and weight-loss interventions can help improve mental health, but there is conflicting evidence regarding their efficacy; and moreover, there is substantial interindividual heterogeneity that needs to be understood. We aimed to identify genetic and gut microbiome factors that explain interindividual differences in mental health improvement after a dietary and lifestyle intervention for weight loss. We recruited 369 individuals participating in Digbi Health’s personalized digital therapeutics care program and evaluated the association of 23 genetic scores, the abundance of 178 gut microbial genera, and 42 bacterial pathways with mental health. We studied the presence/absence of anxiety or depression, or sleep problems at baseline and improvement on anxiety, depression, and insomnia after losing at least 2% body weight. Participants lost on average 5.4% body weight and >95% reported improving mental health symptom intensity. There were statistically significant correlations between: (a) genetic scores with anxiety or depression at baseline, gut microbial functions with sleep problems at baseline, and (b) genetic scores and gut microbial taxa and functions with anxiety, depression, and insomnia improvement. Our results are concordant with previous findings, including the association between anxiety or depression at baseline with genetic scores for alcohol use disorder and major depressive disorder. As well, our results uncovered new associations in line with previous epidemiological literature. As evident from previous literature, we also observed associations of gut microbial signatures with mental health including short-chain fatty acids and bacterial neurotoxic metabolites specifically with depression. Our results also show that microbiome and genetic factors explain self-reported mental health status and improvement better than demographic variables independently. The genetic and microbiome factors identified in this study provide the basis for designing and personalizing dietary interventions to improve mental health.

Genetic variables of the glutamatergic system associated with treatment-resistant depression: A review of the literature

Depression is a common, recurrent mental disorder and one of the leading causes of disability and global burden of disease worldwide. Up to 15%-40% of cases do not respond to diverse pharmacological treatments and, thus, can be defined as treatment-resistant depression (TRD). The development of biomarkers predictive of drug response could guide us towards personalized and earlier treatment. Growing evidence points to the involvement of the glutamatergic system in the pathogenesis of TRD. Specifically, the N-methyl-D-aspartic acid receptor (NMDAR) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR), which are targeted by ketamine and esketamine, are proposed as promising pathways. A literature search was performed to identify studies on the genetics of the glutamatergic system in depression, focused on variables related to NMDARs and AMPARs. Our review highlights GRIN2B, which encodes the NR2B subunit of NMDAR, as a candidate gene in the pathogenesis of TRD. In addition, several studies have associated genes encoding AMPAR subunits with symptomatic severity and suicidal ideation. These genes encoding glutamatergic receptors could, therefore, be candidate genes for understanding the etiopathogenesis of TRD, as well as for understanding the pharmacodynamic mechanisms and response to ketamine and esketamine treatment.

Metabotropic Glutamate Receptor 5 in Amygdala Target Neurons Regulates Susceptibility to Chronic Social Stress

BACKGROUND

Metabotropic glutamate receptor 5 (mGluR5) has been implicated in stress-related psychiatric disorders, particularly major depressive disorder. Although growing evidence supports the proresilient role of mGluR5 in corticolimbic circuitry in the depressive-like behaviors following chronic stress exposure, the underlying neural mechanisms, including circuits and molecules, remain unknown.

METHODS

We measured the c-Fos expression and probability of neurotransmitter release in and from basolateral amygdala (BLA) neurons projecting to the medial prefrontal cortex (mPFC) and to the ventral hippocampus (vHPC) after chronic social defeat stress. The role of BLA projections in depressive-like behaviors was assessed using optogenetic manipulations, and the underlying molecular mechanisms of mGluR5 and downstream signaling were investigated by Western blotting, viral-mediated gene transfer, and pharmacological manipulations.

RESULTS

Chronic social defeat stress disrupted neural activity and glutamatergic transmission in both BLA projections. Optogenetic activation of BLA projections reversed the detrimental effects of chronic social defeat stress on depressive-like behaviors and mGluR5 expression in the mPFC and vHPC. Conversely, inhibition of BLA projections of mice undergoing subthreshold social defeat stress induced a susceptible phenotype and mGluR5 reduction. These two BLA circuits appeared to act in an independent way. We demonstrate that mGluR5 overexpression in the mPFC or vHPC was proresilient while the mGluR5 knockdown was prosusceptible and that the proresilient effects of mGluR5 are mediated through distinctive downstream signaling pathways in the mPFC and vHPC.

CONCLUSIONS

These findings identify mGluR5 in the mPFC and vHPC that receive BLA inputs as a critical mediator of stress resilience, highlighting circuit-specific signaling for depressive-like behaviors.

Joint Exposure to Positive Affect, Life Satisfaction, Depressive Symptoms, and Neuroticism and Incident Type 2 Diabetes

CONTEXT

Whether the psychological wellbeing status could be a risk factor for type 2 diabetes is unclear.

OBJECTIVE

We aimed to measure the association between combined psychological wellbeing factors and type 2 diabetes and investigate whether this association was modified by genetic predisposition.

METHODS

Prospective cohort study from the UK Biobank. In total, 127 496 participants who completed a psychological wellbeing questionnaire and did not have type 2 diabetes at baseline (2006-2010) were included; among them, 88 584 (69.5%) were analyzed to determine their genetic predisposition. The main outcome measure was incident type 2 diabetes.

RESULTS

During the median follow-up of 10.0 years, 2547 incident type 2 diabetes cases were documented. Moderate to extreme unhappiness, satisfaction score ≤3, presence of broad depression, and a neuroticism score ≥3 were all significantly and independently associated with an increased risk of diabetes. When considered as a combination indicator, compared with individuals in the highest quartile of the psychological wellbeing score, the fully adjusted hazard ratios (95% CI) of type 2 diabetes were 1.41 (1.21-1.65) in the third quartile, 1.45 (1.24-1.69) in the second quartile, and 1.73 (1.48-2.01) in the lowest quartile. In the stratified analysis, we observed significant interactions between age and physical activity, and type 2 diabetes (Pinteraction < .001 and 0.049, respectively). However, there was no significant interaction between the psychological wellbeing score and genetic susceptibility to diabetes (Pinteraction = .980).

CONCLUSION

Worse overall psychological wellbeing was associated with a significantly increased risk of type 2 diabetes in a dose-response fashion regardless of genetic predisposition.

Causal Effect of Age at Menarche on the Risk for Depression: Results From a Two-Sample Multivariable Mendelian Randomization Study

A fair number of epidemiological studies suggest that age at menarche (AAM) is associated with depression, but the reported effect sizes are small, and there is evidence of residual confounding. Moreover, previous Mendelian randomization (MR) studies to avoid inferential problems inherent to epidemiological studies have provided mixed findings. To clarify the causal relationship between age at menarche and broadly defined depression risk, we used 360 genome-wide significantly AAM-related single-nucleotide polymorphisms (SNPs) as instrumental variable and data from the latest GWAS for the broadly defined depression risk on 807,553 individuals (246,363 cases and 561,190 controls). Multiple methods to account for heterogeneity of the instrumental variable (penalized weighted median, MR Lasso, and contamination mixture method), systematic and idiosyncratic pleiotropy (MR RAPS), and horizontal pleiotropy (MR PRESSO and multivariable MR using three methods) were used. Body mass index, education attainment, and total white blood count were considered pleiotropic phenotypes in the multivariable MR analysis. In the univariable [inverse-variance weighted (IVW): OR = 0.96, 95% confidence interval = 0.94–0.98, p = 0.0003] and multivariable MR analysis (IVW: OR = 0.96, 95% confidence interval = 0.94–0.99, p = 0.007), there was a significant causal effect of AAM on depression risk. Thus, the present study supports conclusions from previous epidemiological studies implicating AAM in depression without the pitfalls of residual confounding and reverse causation. Considering the adverse consequences of an earlier AAM on mental health, this finding should foster efforts to address risk factors that promote an earlier AAM.

Red Raspberry Extract Decreases Depression-Like Behavior in Rats by Modulating Neuroinflammation and Oxidative Stress

Objective

Red raspberry serves as a proven natural product to produce anti-inflammatory, antioxidant, and anticancer functions, but limited findings are available on its effects on depression. This study, by using a chronic unpredictable mild stress- (CUMS-) induced depression model, thus investigated the effects and underlying mechanism of red raspberry extract (RRE) on depressive behavior, inflammation, and oxidative stress.

Methods

Different treatments were given after random grouping of Sprague-Dawley rats, including no intervention (control), CUMS induction, and CUMS+different concentrations of RRE, and subsequently, depression-like behavior tests were performed. HE staining was designed to observe the pathological damage of the hippocampal tissue in rats. The levels of oxidative stress, endocrine hormones, and inflammatory factors were determined by biochemical assay and ELISA, and gene expression (mRNA and protein) in the hippocampal tissue by qRT-PCR and Western blot.

Results

On completion of CUMS treatment, the rats showed severe depression-like behavior, with obvious hippocampal tissue damage, oxidative inflammatory response, and endocrine imbalance. Importantly, RRE treatment significantly improved such depression-like behavior and attenuated histopathological damage in CUMS rats when reducing inflammation and oxidative stress and endocrine imbalance with upregulation of glutathione (GSH), superoxide dismutase (SOD), and interleukin- (IL-) 10 and downregulation of adrenocorticotropic hormone (ACTH), corticosterone (CORT), malondialdehyde (MDA), IL-1β, cyclooxygenase- (COX-) 2, and human macrophage chemoattractant protein- (MCP-) 1. In addition, for CUMS rats, RRE was a contributor to increasingly expressed brain-derived neurotrophic factor (BDNF), neurotrophic tyrosine receptor kinase 2 (TrkB), and p-mTOR but inhibited p-GSK-3β expression in the hippocampal tissue. All the above antidepressant effects of RRE were concentration-dependent.

Conclusion

By regulating neuroinflammation, oxidative stress response, endocrine level, and BDNF/TrkB level, RRE showed potential efficacy in alleviating depression-like behavior and histopathological damage of hippocampal tissue in CUMS rats by regulating the GSK3β and mTOR signaling pathways.

Associations between depression-relevant genetic risk and youth stress exposure: Evidence of gene-environment correlations

Familial risk for depression is associated with youth exposure to self-generated dependent stressful life events and independent events that are out of youth's control. Familial risk includes both genetic and environmental influences, raising the question of whether genetic influences, specifically, are associated with youth exposure to both dependent and independent stressful life events. To address this question, this study examined the relation between a genome-wide association study (GWAS)-derived depression-based polygenic risk score (DEP-PRS) and youth experiences of dependent and independent stress. Participants were 180 youth (ages 8 to 14, 52.2% female) of European ancestry and their biological mothers recruited based on the presence versus absence of a history of major depressive disorder (MDD) in the mothers. Youth and mothers were interviewed every 6 months for 2 years regarding the occurrence of stressful life events, which were coded as independent or dependent (self-generated). Results indicated that youth's DEP-PRS and maternal history of MDD were uniquely associated with increased exposure to both dependent and independent events. Similar results were observed when examining major versus minor events separately, with the additional finding of a DEP-PRS × mother MDD interaction for major dependent events such that levels of moderate to severe dependent life stressors were highest among youth with high DEP-PRSs who also had mothers with MDD. These results not only support the presence of depression-relevant gene-environment correlations (rGEs), but also highlight the possibility that rather than only capturing depression-specific genetic liability, GWAS-derived polygenic risk scores may also capture genetic variance contributing to stress exposure. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Evaluation of bi-directional causal association between depression and cardiovascular diseases: a Mendelian randomization study

BACKGROUND

Depression and cardiovascular disease (CVD) are associated with each other but their relationship remains unclear. We aim to determine whether genetic predisposition to depression are causally linked to CVD [including coronary artery disease (CAD), myocardial infarction (MI), stroke and atrial fibrillation (AF)].

METHODS

Using summary statistics from the largest genome-wide association studies (GWAS) or GWAS meta-analysis of depression (primary analysis: n = 500 199), broad depression (help-seeking behavior for problems with nerves, anxiety, tension or depression; secondary analysis: n = 322 580), CAD (n = 184 305), MI (n = 171 875), stroke (n = 446 696) and AF (n = 1 030 836), genetic correlation was tested between two depression phenotypes and CVD [MI, stroke and AF (not CAD as its correlation was previously confirmed)]. Causality was inferred between correlated traits by Mendelian Randomization analyses.

RESULTS

Both depression phenotypes were genetically correlated with MI (depression: r_G = 0.169; p = 9.03 × 10^-9; broad depression: r_G = 0.123; p = 1 × 10^-4) and AF (depression: r_G = 0.112; p = 7.80 × 10^-6; broad depression: r_G = 0.126; p = 3.62 × 10^-6). Genetically doubling the odds of depression was causally associated with increased risk of CAD (OR = 1.099; 95% CI 1.031-1.170; p = 0.004) and MI (OR = 1.146; 95% CI 1.070-1.228; p = 1.05 × 10^-4). Adjustment for blood lipid levels/smoking status attenuated the causality between depression and CAD/MI. Null causal association was observed for CVD on depression. A similar pattern of results was observed in the secondary analysis for broad depression.

CONCLUSIONS

Genetic predisposition to depression may have positive causal roles on CAD/MI. Genetic susceptibility to self-awareness of mood problems may be a strong causal risk factor of CAD/MI. Blood lipid levels and smoking may potentially mediate the causal pathway. Prevention and early diagnosis of depression are important in the management of CAD/MI.

Total Saikosaponins Attenuates Depression-Like Behaviors Induced by Chronic Unpredictable Mild Stress in Rats by Regulating the PI3K/AKT/NF-κB Signaling Axis

Background

Depression is a major cause of disability and most antidepressant medicines are ineffective owing to their high toxicity and numerous adverse effects. As a result, there is an urgent need to find new effective treatment methods. This paper aims to investigate the effect and mechanism of total saikosaponins (TSS) on depression-like behaviors induced by chronic unpredictable mild stress (CUMS) in rats.

Methods

Twenty-four male SD rats were randomly divided into 4 groups: control group, CUMS group, TSS group, and fluoxetine (Flu) group. Then, the following tests were conducted: sucrose preference test, open field test, and elevated plus maze test. Additionally, ELISA was used to detect the levels of corticosterone (CORT) and adrenocorticotropic hormone (ACTH) in the serum of the rats as well as the levels of inflammatory cytokines IL-1β, IL-6, and TNF-α in the hippocampus, and Western blot was used for measuring the expression of brain-derived neurotrophic factor (BDNF) protein and related proteins of the PI3K/AKT/NF-κB signaling pathway in the hippocampus.

Results

TSS could significantly improve rat behaviors, specifically indicated by increases in sucrose preference, total movement distance, stay time in the central area, number of entries into open arms, time spent in open arms, and a decrease in stay time in the peripheral area. TSS acted to significantly reduce BDNF protein expression and increase the contents of ACTH and CORT in serum as well as the levels of IL-1β, IL-6, and TNF-α in the hippocampal tissue in rats. In addition, it was able to raise the ratios of p-PI3K/PI3K and p-AKT/AKT and decrease the ratio of p-p65/p65 in tissues, which in turn regulated the PI3K/AKT/NF-κB signaling pathway.

Conclusions

TSS, through regulating PI3K/AKT/NF-κB signaling axis, can alleviate depression-like behaviors and elevate neuroendocrine hormone levels and inflammatory factor levels.

Mendelian randomization analysis for attention deficit/hyperactivity disorder: studying a broad range of exposures and outcomes

BACKGROUND

Attention deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder caused by a combination of genetic and environmental factors and is often thought as an entry point into a negative life trajectory, including risk for comorbid disorders, poor educational achievement or low income. In the present study, we aimed to clarify the causal relationship between ADHD and a comprehensive range of related traits.

METHODS

We used genome-wide association study (GWAS) summary statistics for ADHD (n = 53 293) and 124 traits related to anthropometry, cognitive function and intelligence, early life exposures, education and employment, lifestyle and environment, longevity, neurological, and psychiatric and mental health or personality and psychosocial factors available in the MR-Base database (16 067 ≤n ≤766 345). To investigate their causal relationship with ADHD, we used two-sample Mendelian randomization (MR) with a range of sensitivity analyses, and validated MR findings using causal analysis using summary effect estimates (CAUSE), aiming to avoid potential false-positive results.

RESULTS

Our findings strengthen previous evidence of a causal effect of ADHD liability on smoking and major depression, and are consistent with a causal effect on odds of decreased average total household income [odds ratio (OR) = 0.966, 95% credible interval (CrI) = (0.954, 0.979)] and increased lifetime number of sexual partners [OR = 1.023, 95% CrI = (1.013, 1.033)]. We also found evidence for a causal effect on ADHD for liability of arm predicted mass and weight [OR = 1.452, 95% CrI = (1.307, 1.614) and OR = 1.430, 95% CrI = (1.326, 1.539), respectively] and time spent watching television [OR = 1.862, 95% CrI = (1.545, 2.246)], and evidence for a bidirectional effect for age of first sexual intercourse [beta = -0.058, 95% CrI = (-0.072, -0.044) and OR = 0.413, 95% CrI = (0.372, 0.457), respectively], odds of decreased age completed full-time education [OR = 0.972, 95% CrI = (0.962, 0.981) and OR = 0.435, 95% CrI = (0.356, 0.533), respectively] and years of schooling [beta = -0.036, 95% CrI = (-0.048, -0.024) and OR = 0.458, 95% CrI = (0.411, 0.511), respectively].

CONCLUSIONS

Our results may contribute to explain part of the widespread co-occurring traits and comorbid disorders across the lifespan of individuals with ADHD and may open new opportunities for developing preventive strategies for ADHD and for negative ADHD trajectories.

The molecular pathophysiology of mood disorders: From the analysis of single molecular layers to multi-omic integration

Next-generation sequencing now enables the rapid and affordable production of reliable biological data at multiple molecular levels, collectively referred to as "omics". To maximize the potential for discovery, computational biologists have created and adapted integrative multi-omic analytical methods. When applied to diseases with traceable pathophysiology such as cancer, these new algorithms and statistical approaches have enabled the discovery of clinically relevant molecular mechanisms and biomarkers. In contrast, these methods have been much less applied to the field of molecular psychiatry, although diagnostic and prognostic biomarkers are similarly needed. In the present review, we first briefly summarize main findings from two decades of studies that investigated single molecular processes in relation to mood disorders. Then, we conduct a systematic review of multi-omic strategies that have been proposed and used more recently. We also list databases and types of data available to researchers for future work. Finally, we present the newest methodologies that have been employed for multi-omics integration in other medical fields, and discuss their potential for molecular psychiatry studies.

Identifying causal genes for depression via integration of the proteome and transcriptome from brain and blood

Genome-wide association studies (GWASs) have identified numerous risk genes for depression. Nevertheless, genes crucial for understanding the molecular mechanisms of depression and effective antidepressant drug targets are largely unknown. Addressing this, we aimed to highlight potentially causal genes by systematically integrating the brain and blood protein and expression quantitative trait loci (QTL) data with a depression GWAS dataset via a statistical framework including Mendelian randomization (MR), Bayesian colocalization, and Steiger filtering analysis. In summary, we identified three candidate genes (TMEM106B, RAB27B, and GMPPB) based on brain data and two genes (TMEM106B and NEGR1) based on blood data with consistent robust evidence at both the protein and transcriptional levels. Furthermore, the protein-protein interaction (PPI) network provided new insights into the interaction between brain and blood in depression. Collectively, four genes (TMEM106B, RAB27B, GMPPB, and NEGR1) affect depression by influencing protein and gene expression level, which could guide future researches on candidate genes investigations in animal studies as well as prioritize antidepressant drug targets.

Multitrait genetic association analysis identifies 50 new risk loci for gastro-oesophageal reflux, seven new loci for Barrett's oesophagus and provides insights into clinical heterogeneity in reflux diagnosis

OBJECTIVE

Gastro-oesophageal reflux disease (GERD) has heterogeneous aetiology primarily attributable to its symptom-based definitions. GERD genome-wide association studies (GWASs) have shown strong genetic overlaps with established risk factors such as obesity and depression. We hypothesised that the shared genetic architecture between GERD and these risk factors can be leveraged to (1) identify new GERD and Barrett's oesophagus (BE) risk loci and (2) explore potentially heterogeneous pathways leading to GERD and oesophageal complications.

DESIGN

We applied multitrait GWAS models combining GERD (78 707 cases; 288 734 controls) and genetically correlated traits including education attainment, depression and body mass index. We also used multitrait analysis to identify BE risk loci. Top hits were replicated in 23andMe (462 753 GERD cases, 24 099 BE cases, 1 484 025 controls). We additionally dissected the GERD loci into obesity-driven and depression-driven subgroups. These subgroups were investigated to determine how they relate to tissue-specific gene expression and to risk of serious oesophageal disease (BE and/or oesophageal adenocarcinoma, EA).

RESULTS

We identified 88 loci associated with GERD, with 59 replicating in 23andMe after multiple testing corrections. Our BE analysis identified seven novel loci. Additionally we showed that only the obesity-driven GERD loci (but not the depression-driven loci) were associated with genes enriched in oesophageal tissues and successfully predicted BE/EA.

CONCLUSION

Our multitrait model identified many novel risk loci for GERD and BE. We present strong evidence for a genetic underpinning of disease heterogeneity in GERD and show that GERD loci associated with depressive symptoms are not strong predictors of BE/EA relative to obesity-driven GERD loci.

Shared genetic loci between depression and cardiometabolic traits

Epidemiological and clinical studies have found associations between depression and cardiovascular disease risk factors, and coronary artery disease patients with depression have worse prognosis. The genetic relationship between depression and these cardiovascular phenotypes is not known. We here investigated overlap at the genome-wide level and in individual loci between depression, coronary artery disease and cardiovascular risk factors. We used the bivariate causal mixture model (MiXeR) to quantify genome-wide polygenic overlap and the conditional/conjunctional false discovery rate (pleioFDR) method to identify shared loci, based on genome-wide association study summary statistics on depression (n = 450,619), coronary artery disease (n = 502,713) and nine cardiovascular risk factors (n = 204,402–776,078). Genetic loci were functionally annotated using FUnctional Mapping and Annotation (FUMA). Of 13.9K variants influencing depression, 9.5K (SD 1.0K) were shared with body-mass index. Of 4.4K variants influencing systolic blood pressure, 2K were shared with depression. ConjFDR identified 79 unique loci associated with depression and coronary artery disease or cardiovascular risk factors. Six genomic loci were associated jointly with depression and coronary artery disease, 69 with blood pressure, 49 with lipids, 9 with type 2 diabetes and 8 with c-reactive protein at conjFDR < 0.05. Loci associated with increased risk for depression were also associated with increased risk of coronary artery disease and higher total cholesterol, low-density lipoprotein and c-reactive protein levels, while there was a mixed pattern of effect direction for the other risk factors. Functional analyses of the shared loci implicated metabolism of alpha-linolenic acid pathway for type 2 diabetes. Our results showed polygenic overlap between depression, coronary artery disease and several cardiovascular risk factors and suggest molecular mechanisms underlying the association between depression and increased cardiovascular disease risk.

Depression and Inflammatory Bowel Disease: A Bidirectional Two-sample Mendelian Randomization Study

BACKGROUND AND AIMS

Observational studies have suggested a bidirectional association between depression and inflammatory bowel disease [IBD], including Crohn's disease [CD] and ulcerative colitis [UC]. However, it remains unclear whether the observed associations are causal due to the difficulties of determining sequential temporality. We investigated the association between depression and IBD by using bidirectional two-sample Mendelian randomization [MR].

METHODS

Independent genetic variants for depression and IBD were selected as instruments from published genome-wide association studies [GWAS] among individuals of predominantly European ancestry. Summary statistics for instrument-outcome associations were retrieved from three separate databases for both depression [Psychiatric Genomics Consortium, FinnGen and UK Biobank] and IBD [the largest GWAS meta-analysis, FinnGen and UK Biobank], respectively. MR analyses included the inverse-variance-weighted method, weighted-median estimator, MR-Egger regression, and sensitivity analyses of Steiger filtering and MR PRESSO. From either direction, analyses were performed per outcome database and were subsequently meta-analysed using a fixed-effect model.

RESULTS

Genetically predicted depression [per log-odds ratio increase] was associated with a higher risk of IBD; odds ratios [95% confidence interval] for IBD, CD and UC were 1.20 [1.05, 1.36], 1.29 [1.07, 1.56] and 1.22 [1.01, 1.47] in a combined sample size of 693 183 [36 507 IBD cases], 212 172 [13 714 CD cases] and 219 686 [15 691 UC cases] individuals, respectively. In contrast, no association was observed between genetically influenced IBD and depression in 534 635 individuals [71 466 depression cases].

CONCLUSIONS

Our findings corroborated a causal association of depression on IBD, which may impact the clinical decision on the management of depression in patients with IBD. Though our results did not support a causal effect of IBD on depression, further investigations are needed to clarify the effect of IBD activity on depression [with different symptomology].

Shared genetic links between frontotemporal dementia and psychiatric disorders

BACKGROUND

Epidemiological and clinical studies have suggested comorbidity between frontotemporal dementia (FTD) and psychiatric disorders. FTD patients carrying specific mutations were at higher risk for some psychiatric disorders, and vice versa, implying potential shared genetic etiology, which is still less explored.

METHODS

We examined the genetic correlation using summary statistics from genome-wide association studies and analyzed their genetic enrichment leveraging the conditional false discovery rate method. Furthermore, we explored the causal association between FTD and psychiatric disorders with Mendelian randomization (MR) analysis.

RESULTS

We identified a significant genetic correlation between FTD and schizophrenia at both genetic and transcriptomic levels. Meanwhile, robust genetic enrichment was observed between FTD and schizophrenia and alcohol use disorder. Seven shared genetic loci were identified, which were mainly involved in interleukin-induced signaling, synaptic vesicle, and brain-derived neurotrophic factor signaling pathways. By integrating cis-expression quantitative trait loci analysis, we identified MAPT and CADM2 as shared risk genes. MR analysis showed mutual causation between FTD and schizophrenia with nominal association.

CONCLUSIONS

Our findings provide evidence of shared etiology between FTD and schizophrenia and indicate potential common molecular mechanisms contributing to the overlapping pathophysiological and clinical characteristics. Our results also demonstrate the essential role of autoimmunity in these diseases. These findings provide a better understanding of the pleiotropy between FTD and psychiatric disorders and have implications for therapeutic trials.

Increased genetic contribution to wellbeing during the COVID-19 pandemic

Physical and mental health are determined by an interplay between nature, for example genetics, and nurture, which encompasses experiences and exposures that can be short or long-lasting. The COVID-19 pandemic represents a unique situation in which whole communities were suddenly and simultaneously exposed to both the virus and the societal changes required to combat the virus. We studied 27,537 population-based biobank participants for whom we have genetic data and extensive longitudinal data collected via 19 questionnaires over 10 months, starting in March 2020. This allowed us to explore the interaction between genetics and the impact of the COVID-19 pandemic on individuals' wellbeing over time. We observe that genetics affected many aspects of wellbeing, but also that its impact on several phenotypes changed over time. Over the course of the pandemic, we observed that the genetic predisposition to life satisfaction had an increasing influence on perceived quality of life. We also estimated heritability and the proportion of variance explained by shared environment using variance components methods based on pedigree information and household composition. The results suggest that people's genetic constitution manifested more prominently over time, potentially due to social isolation driven by strict COVID-19 containment measures. Overall, our findings demonstrate that the relative contribution of genetic variation to complex phenotypes is dynamic rather than static.

Associations of PM2.5 and road traffic noise with mental health: Evidence from UK Biobank

BACKGROUND

The associations of atmospheric particulate matter with diameters of 2.5 μm or less (PM2.5) and road traffic noise with mental disorders in men and women are not well studied.

OBJECTIVES

We aim to examine the cross-sectional associations of PM2.5 and road traffic noise with mental disorders in men and women.

METHODS

The baseline data of the UK Biobank study (2006-2010) were used. Mental disorders including symptoms of nerves, anxiety, tension or depression (NATD), major depression, and bipolar disorder were assessed by validated questions. Verified models were used to estimate PM2.5 and road traffic noise.

RESULTS

A total of 334,986 participants with measurements of NATD and 90,706 participants with measurements of major depression and bipolar disorder were included in the analysis. After adjusting for covariates, the odds for the risk of NATD symptoms increased by 2.31 (95% CI: 2.15-2.50) times per 10 μg/m³ increase in PM2.5. The odds for the risk of major depression and bipolar disorder increased by 2.26 and 4.99 times per 10 μg/m³ increase in PM2.5. On the other hand, higher road traffic noise exposure was significantly associated with a higher risk of NATD symptoms (Decile 6-8 (54.9-57.8 dB), OR: 1.03, 95% CI: 1.01-1.06; Decile 9-10 (≥57.8 dB), OR: 1.04, 95% CI: 1.01-1.07) and bipolar disorder (Decile 2-5 (52.1-54.9 dB), OR: 1.26, 95% CI: 1.00-1.59; Decile 6-8 (54.9-57.8 dB), OR: 1.30, 95% CI: 1.02-1.65; Decile 9-10 (≥57.8 dB), OR: 1.54, 95% CI: 1.21-1.97). Interestingly, a negative association was observed between moderate road traffic noise and major depression (Decile 2-5 (52.1-54.9 dB), OR: 0.95, 95% CI: 0.90-1.00). Interactions between PM2.5 exposure with age, gender, and sleeplessness for NATD symptoms were observed (P < 0.05), while interactions between road traffic noise exposure with age and gender were observed (P < 0.05).

CONCLUSIONS

We found a positive association between PM2.5 and mental disorders. Meanwhile, we found a positive association of road traffic noise with NATD symptoms and bipolar disorder and a negative association of moderate road traffic noise with major depression. Also, the effect modifications of these associations by age, gender, or sleeplessness may exist.