Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

Causal relationship between gut microbiota, lipids, and neuropsychiatric disorders: A Mendelian randomization mediation study

BACKGROUND

Numerous studies have shown an interconnection between the gut microbiota and the brain via the "gut-brain" axis. However, the causal relationships between gut microbiota, lipids, and neuropsychiatric disorders remain unclear. This study aimed to analyze potential associations among gut microbiota, lipids, and neuropsychiatric disorders-including AD, PD, ALS, MS, SCZ, MDD, and BD-using summary data from large-scale GWAS.

METHODS

Bidirectional Mendelian randomization (MR) with inverse variance weighting (IVW) was the primary method. Supplementary analyses included sensitivity analyses, Steiger tests, and Bayesian weighted MR (BWMR). Mediation analyses used two-step MR (TSMR) and multivariable MR (MVMR).

RESULTS

The analyses revealed 51 positive correlations (risk factors) (β > 0, P < 0.05) and 47 negative correlations (protective factors) (β < 0, P < 0.05) between gut microbiota and neuropsychiatric disorders. In addition, 35 positive correlations (β > 0, P < 0.05) and 22 negative correlations (β < 0, P < 0.05) between lipids and neuropsychiatric disorders were observed. Assessment of reverse causality with the seven neuropsychiatric disorders as exposures and the identified gut microbiota and lipids as outcomes revealed no evidence of reverse causality (P > 0.05). Mediation analysis indicated that the effect of the species Bacteroides plebeius on MDD is partially mediated through the regulation of phosphatidylcholine (16:0_20:4) levels (mediation proportion = 10.9 % [95 % CI = 0.0110-0.2073]).

CONCLUSION

This study provides evidence of a causal relationship between gut microbiota and neuropsychiatric disorders, suggesting lipids as mediators. These findings offer new insights into the mechanisms by which gut microbiota may influence neuropsychiatric disorders.

Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder

BACKGROUND

Early diagnosis and treatment of mental illnesses is hampered by the lack of reliable markers. This study used machine learning models to uncover diagnostic and risk prediction markers for eating disorders (EDs), major depressive disorder (MDD), and alcohol use disorder (AUD).

METHODS

Case-control samples (aged 18-25 years), including participants with Anorexia Nervosa (AN), Bulimia Nervosa (BN), MDD, AUD, and matched controls, were used for diagnostic classification. For risk prediction, we used a longitudinal population-based sample (IMAGEN study), assessing adolescents at ages 14, 16 and 19. Regularized logistic regression models incorporated broad data domains spanning psychopathology, personality, cognition, substance use, and environment.

RESULTS

The classification of EDs was highly accurate, even when excluding body mass index from the analysis. The area under the receiver operating characteristic curves (AUC-ROC [95 % CI]) reached 0.92 [0.86-0.97] for AN and 0.91 [0.85-0.96] for BN. The classification accuracies for MDD (0.91 [0.88-0.94]) and AUD (0.80 [0.74-0.85]) were also high. The models demonstrated high transdiagnostic potential, as those trained for EDs were also accurate in classifying AUD and MDD from healthy controls, and vice versa (AUC-ROCs, 0.75-0.93). Shared predictors, such as neuroticism, hopelessness, and symptoms of attention-deficit/hyperactivity disorder, were identified as reliable classifiers. In the longitudinal population sample, the models exhibited moderate performance in predicting the development of future ED symptoms (0.71 [0.67-0.75]), depressive symptoms (0.64 [0.60-0.68]), and harmful drinking (0.67 [0.64-0.70]).

CONCLUSIONS

Our findings demonstrate the potential of combining multi-domain data for precise diagnostic and risk prediction applications in psychiatry.

Mediating effects of gastroesophageal reflux disease and smoking behavior on the relationship between depression and chronic obstructive pulmonary disease: Trans-ethnic Mendelian randomization study

BACKGROUND

This study seeks to elucidate the association between depression and the risk of chronic obstructive pulmonary disease (COPD) by Mendelian randomization (MR) analysis, motivated by prior observational studies indicating a potential link between these conditions.

METHODS

Data from individuals of European (EUR) and East Asian (EAS) ancestries diagnosed with major depressive disorder (MDD) were selected for analysis. The primary method utilized was inverse variance weighted (IVW) method, supplemented by a series of sensitivity analyses and false discovery rate (FDR) corrections. Subsequently, multivariable and mediation MR analyses were conducted to assess the impact of potential confounders and their mediating effects.

RESULTS

IVW revealed a significant causal relationship between MDD and COPD within EUR ancestry (OR 1.425, 95 % CI 1.243-1.633, P = 3.56 × 10-7, PFDR = 2.14 × 10-6). Additionally, replication datasets provided consistent evidence for these causal associations. Multivariable and mediation MR analyses identified gastroesophageal reflux disease (GORD) as a complete mediator (mediation effect: 98.97 %, P = 1.38 × 10-15), while smoking initiation (SI) (26.30 %, 5.54 × 10-9), age of smoking initiation (ASI) (18.73 %, 0.019), and cigarettes per day (CPD) (18.72 %, 0.004) were identified as partial mediators of this causal relationship. No causal association was detected in EAS ancestry, nor was reverse analysis.

CONCLUSIONS

This study established a causal relationship between MDD and COPD risk in EUR ancestry, identifying GORD and smoking as pivotal mediators. Future research involving larger cohorts is essential to validate the generalizability of these findings across other ancestries.

Associations between major depressive disorders and Parkinson's Disease and impact of their comorbidity sequence

BACKGROUND

The comorbidity of major depressive disorder (MDD) and Parkinson's disease (PD) were prevalent and has a profound impact on patients. However, whether this comorbidity results from specific pathological processes or a mutual cause-and-effect relationship was largely controversial. Additionally, although MDD can appear before or after PD, the health impact of the comorbidity sequence is poorly understood.

METHODS

We used mendelian randomization (MR) and UK biobank (UKB) cohort to explore the associations between MDD and PD. MR was also utilized to investigate potential confounders. By classifying UKB patients into MDD first and PD first groups, we evaluated the health impact of the comorbidity sequence using Cox regression.

RESULTS

Bidirectional MR and cohort study showed conflicting results. MR did not find associations between MDD followed by PD (odds ratio [OR] = 1.28, 95 % confidence interval [CI] = 0.85-1.94) or PD followed by MDD (OR = 0.99, 95 % CI = 0.97-1.01). However, the cohort study found a significant effect of MDD on PD (hazard ratio [HR] = 1.75, 95 % CI = 1.55-1.97) and PD on MDD (HR = 4.35, 95 % CI = 3.65-5.19). By performing MR on 4709 proteins, we identified ESD, LEAP2, NDRG3, NRXN3, and PLXNB2 as potential common causes of MDD and PD. Additionally, PD first group had higher risks of all-cause mortality (HR = 1.65, 95 % CI = 1.03-1.90), dementia (HR = 1.88, 95 % CI = 1.16-3.04), and aspiration pneumonia (HR = 1.89, 95 % CI = 1.09-3.27).

CONCLUSIONS

Our study suggested the comorbidity of MDD and PD is likely the result of certain pathological processes. Additionally, patients with PD first had higher risks of several adverse outcomes.

Impact of marine heatwaves on Carcinus maenas crabs: Physiological and biochemical mechanisms of thermal stress resilience

Marine heatwaves (MHWs), characterized by prolonged periods of elevated sea temperatures, pose significant threats to marine ecosystems, particularly affecting the physiology and behavior of marine organisms, including crustaceans. This study investigates the physiological and biochemical responses of males and females of Carcinus maenas crabs, after an acute exposure to an MHW, focusing on energy metabolism, oxidative status, and potential neurotoxicity. Specimens were exposed to controlled laboratory conditions simulating a temperature increase from 17 °C to 23 °C, and responses were analyzed in gills and hepatopancreas. Results revealed sex-specific differences in thermal stress resilience, with males showing higher glycogen storage in gills after MHW exposure, while females exhibited a significant reduction in glycogen reserves and an increase in antioxidant enzyme activity. Superoxide dismutase and glutathione reductase activities were notably elevated in females subjected to MHW, suggesting a more robust antioxidant response to counteract oxidative stress. Additionally, acetylcholinesterase activity, an indicator of neurotoxicity, was significantly reduced in females post-MHW, hinting at potential neurotoxic effects. Despite these biochemical changes, lipid peroxidation levels remained stable across both sexes and tissues, indicating that short-term MHW exposure did not cause significant oxidative damage to cell membranes. This study highlights the importance of considering sex differences in assessing the impacts of climate change-induced stressors on marine organisms, as males and females display distinct metabolic and physiological strategies for coping with thermal stress.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Major depressive disorder and the development of cerebral small vessel disease: A Mendelian randomization study

BACKGROUND

Although observational studies indicate a complex, bidirectional association between major depressive disorder (MDD) and cerebral small vessel disease (CSVD), the results are frequently inconsistent. This study investigated the potential correlation of MDD with both CSVD clinical outcomes and radiological markers, utilizing a bidirectional Mendelian randomization (MR) study design.

METHODS

Instrumental variables for MDD were obtained from the latest and largest genome-wide association study (GWAS). For CSVD, we extracted genetic instruments from GWAS datasets corresponding to both clinical outcomes and radiological markers, including intracerebral hemorrhage, small vessel ischemic stroke, white matter hyperintensities volume, mean diffusivity (MD), fractional anisotropy, brain microbleeds, and enlarged perivascular space (PVS). We employed the inverse variance weighting method as the primary analysis, complemented by conducting extensive sensitivity and heterogeneity tests.

RESULTS

In the forward MR analyses, we discovered that the genetically predicted risk of MDD exhibits a potential causal relationship with two CSVD phenotypes demonstrating microscopic white matter (WM) damage: mean diffusivity (β = 0.784, 95 % CI 0.285-1.283, p = 0.002) and WM-PVS (OR = 1.053, 95%CI 1.010-1.097, p = 0.015). A single SNP (rs2232423) was identified as significantly influencing the causal relationship between MDD and WM. After excluding this SNP, our estimated association between MDD and increased MD (β = 0.516, 95%CI -0.001-1.033, p = 0.048) remained. The effects of MDD on WM-PVS passed all the tests for heterogeneity and pleiotropy. Reverse MR analyses showed no evidence of reverse causality between MDD and an altered CSVD risk.

CONCLUSIONS

This study supports a potential causal association between MDD and CSVD-related indicators of impaired WM microstructure. These insights hold promise for improving risk assessment methods in CSVD.

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

BACKGROUND

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

AIMS

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

Genome-wide association meta-analysis of age at onset of walking in over 70,000 infants of European ancestry

Age at onset of walking is an important early childhood milestone which is used clinically and in public health screening. In this genome-wide association study meta-analysis of age at onset of walking (N = 70,560 European-ancestry infants), we identified 11 independent genome-wide significant loci. SNP-based heritability was 24.13% (95% confidence intervals = 21.86-26.40) with ~11,900 variants accounting for about 90% of it, suggesting high polygenicity. One of these loci, in gene RBL2, co-localized with an expression quantitative trait locus (eQTL) in the brain. Age at onset of walking (in months) was negatively genetically correlated with ADHD and body-mass index, and positively genetically correlated with brain gyrification in both infant and adult brains. The polygenic score showed out-of-sample prediction of 3-5.6%, confirmed as largely due to direct effects in sib-pair analyses, and was separately associated with volume of neonatal brain structures involved in motor control. This study offers biological insights into a key behavioural marker of neurodevelopment.

Relationship Between Problematic Alcohol Use and Various Psychiatric Disorders: A Genetically Informed Study

OBJECTIVE

Problematic alcohol use (PAU) adversely affects the clinical course of psychiatric disorders. Genetic studies have suggested that genetic factors underlie the co-occurrence of PAU with psychiatric disorders. This study aimed to elucidate shared genetic architectures, prioritizing genes that disorders may have in common.

METHODS

Using genome-wide association data of PAU including 435,563 samples from people of European ancestry, this study investigated the genetic relationship between PAU and 11 psychiatric disorders using a bivariate causal mixture model (MiXeR). Local genetic correlation and colocalization analyses were conducted to identify the genomic regions significantly associated with PAU and each psychiatric disorder. Postanalysis included the false discovery rate (FDR) and transcriptome-wide association studies (TWASs), as well as summary-data-based Mendelian randomization to prioritize shared genes by integrating brain transcriptome data.

RESULTS

MiXeR analysis revealed a substantial polygenic overlap (39%-73%) between PAU and psychiatric disorders. Four bivariate genomic regions with high correlations suggest shared causal variants of PAU with major depression and schizophrenia. Within these regions, four and six genes for the PAU-major depression and PAU-schizophrenia pairs, respectively, were mapped by conjunctional FDR analysis. Furthermore, TTC12 and ANKK1 were identified as potential causal genes for PAU and these disorders. The findings were replicated in multi-ancestry analyses of colocalization and TWASs.

CONCLUSIONS

Despite the varying degrees of genetic overlap and directions of shared genetic effect correlations, these results imply the presence of shared genetic factors influencing the comorbidity of PAU and psychiatric disorders. Additionally, TTC12 and ANKK1, located near DRD2, may be causally associated with comorbid conditions.

Identifying novel protein biomarkers with cross-psychiatric disorders effects and potential intervention targets: Evidence from proteomic-Mendelian randomization

Plasma proteins are the potential therapeutic targets for psychiatric disorders due to their important roles in signal transduction. We aimed to explore the plasma protein biomarkers with cross-psychiatric disorders effects. Proteome-wide Mendelian randomization (MR) and colocalization analyses were performed to investigate the potential causal relationship between plasma protein biomarkers and 12 psychiatric disorders and further identify the potential proteins with cross-effects. To assess the directionality and exclude potential reverse causation, Steiger directionality tests and reverse MR analyses were additionally conducted. Then, validation analysis was performed by employing summary data from cross-psychiatric disorder GWAS to validate the cross-psychiatric effects of proteins. Protein-protein interactions were conducted to evaluate the interaction between candidate proteins and druggability assessment was used to prioritize potential drug targets for psychiatric disorders. We identified novel plasma proteins that possessed cross-psychiatric disorder effects, especially BTN2A1 and BTN3A2 associated with major depressive disorder (MDD), schizophrenia (SCZ), and bipolar disorder (BIP); ITIH1, ITIH3, ITIH4 and FES associated with SCZ and BIP, and the cross-effects of these proteins on SCZ and BIP were confirmed by validation analyses. Steiger tests and reverse MR supported causal directionality. Besides, the protein-protein interactions (PPI) analysis indicated cross-effects proteins had significant interaction, especially ITIH1-ITIH3. The druggability assessment prioritized eight proteins, two of which (ITIH3 and NCAM1) has been targeted by antipsychotic drugs. Our findings provided insights into shared biological mechanisms underlying these conditions.

Gamma oscillations as correlates of depression: updating Fitzgerald and Watson (2018)

Depression remains one of the most common and debilitating neuropsychiatric conditions, with little consistency in treatment efficacy. Some of the lack of success in developing effective treatments has been the absence of a reliable biomarker of depression, despite many attempts. One such potential biomarker is the electrical activity of the brain that occurs in the gamma band (30-200 Hz). To evaluate the state of research into gamma as a biomarker of depression, a review of recent research literature was conducted. A total of 31 relevant papers was identified, 22 of which used resting-state studies, and nine included a stimulus-task. These studies were examined here in terms of their definition of gamma, sample sizes, research focus, brain region examined, and EEG methodologies used. Due to the range of methodologies, some inconsistent results emerged but several valuable findings remained, including that depressed patients usually had higher gamma power than their healthy controls (HC), that the imposition of a perceptual task into the research protocol also introduced a strong element of confound to the results, and that studies that sought to evaluate the role of gamma in treatment were yet to be established as reliable. Key issues for future research are discussed, and the potential for gamma as a biomarker of depression is evaluated as emerging.

Hypoxic preconditioning modulates BDNF signaling to alleviate depression-like behaviors in mice and its whole transcriptome sequencing analysis

Depression, a neurological disorder triggered by stressful stimuli such as hypoxia, is associated with high morbidity and mortality. Hypoxic preconditioning (HPC) is an endogenous mechanism that has been used in recent research to upregulate BDNF, a marker of depression, to elicit neuroprotective effects. However, the mechanisms by which HPC protects against depression remain poorly understood. Therefore, this study aimed to investigate the effects of HPC on depressive behaviors via BDNF signaling. Initially, ICR mice were subjected to HPC, followed by the establishment of a 24-hour restraint stress model to mimic depressive behaviors. Subsequent analysis focused on changes in depressive behaviors, biochemical markers, and the levels of BDNF and its ability to modulate synaptic structure and neurogenesis. Furthermore, whole transcriptome sequencing was conducted. The results indicated that HPC relieved characteristic depressive behaviors in restraint stress model mice, regulated neurotransmitter levels, elevated antioxidant capacity, and promoted BDNF signaling in the hippocampus. PSD-95 expression, the number and complexity of neuronal dendritic spines, and hippocampal neurogenesis in model mice were increased via HPC. Restraint stress regulated 373 DElncRNAs, 166 DEcircRNAs, 29 DEmiRNAs and 1235 DEmRNAs, which were also modulated by HPC. The ceRNA networks were constructed on the basis of these DERNAs. Functional enrichment analysis revealed that these genes are related to synapses, neurogenesis and neurotrophin signaling. These results suggested that HPC upregulated BDNF and activated BDNF/PLCγ/CREB signaling to alleviate synaptic deficits and promote hippocampal neurogenesis, ultimately ameliorating depressive behaviors in mice. The identification of various mRNAs and ncRNAs and their constituent ceRNAs provides theoretical guidance for the clinical treatment of depression with HPC.

Timing of physical activity, genetic predisposition, and incident depression: An accelerometer-based prospective cohort study

BACKGROUND

There is a lack of prospective cohort studies exploring the associations between the timing of physical activity and incident depression. This study aimed to explore the associations and to investigate whether genetic predisposition of depression may modify the associations.

METHODS

The study using data from UK Biobank, included 76,218 participants. The data of total physical activity (TPA) and moderate-to-vigorous physical activity (MVPA) were collected by accelerometer measurements over 7 consecutive days. Cox proportional hazard models were performed to calculate the hazard ratio (HR) and 95 % confidence interval (CI).

RESULTS

In total, compared to the midday-afternoon group, participants in the early morning group of TPA had a lower risk of depression (HR: 0.76, 95 % CI: 0.65-0.89). Compared to the inactive group, a lower risk of incident depression was found among the participants with MVPA in the morning (HR: 0.80, 95 % CI: 0.67-0.96) and middy-afternoon (HR: 0.82, 95 % CI: 0.70-0.96). The joint effect analysis of the timing of TPA and genetic predisposition for incident depression showed that compared to the participants with a high genetic predisposition and in the middy-afternoon group of TPA, early morning group had a reduced risk of depression regardless of genetic predisposition. However, in subgroup analyses for genetic predisposition, only participants with a high genetic predisposition to depression benefited from TPA in the early morning.

CONCLUSIONS

TPA in the early morning and MVPA in the morning and middy-afternoon were significantly associated with a lower depression risk, especially for participants with a higher genetic predisposition of depression.

The role of co-occurring conditions and genetics in the associations of eating disorders with attention-deficit/hyperactivity disorder and autism spectrum disorder

Eating disorders (EDs) commonly co-occur with other psychiatric and neurodevelopmental disorders including attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD); however, the pattern of family history and genetic overlap among them requires clarification. This study investigated the diagnostic, familial, and genetic associations of EDs with ADHD and ASD. The nationwide population-based cohort study included all individuals born in Denmark, 1981-2008, linked to their siblings and cousins. Cox regression was used to estimate associations between EDs and ADHD or ASD, and mediation analysis was used to assess the effects of intermediate mood or anxiety disorders. Polygenic scores (PGSs) were used to investigate the genetic association between anorexia nervosa (AN) and ADHD or ASD. Significantly increased risk for any ED was observed following an ADHD or ASD diagnosis. Mediation analysis suggested that intermediate mood or anxiety disorders could account for 44%-100% of the association between ADHD or ASD and ED. Individuals with a full sibling or maternal half sibling with ASD had increased risk of AN compared to those with siblings without ASD. A positive association was found between ASD-PGS and AN risk whereas a negative association was found between AN-PGS and ADHD. In this study, positive phenotypic associations between EDs and ADHD or ASD, mediation by mood or anxiety disorder, and genetic associations between ASD-PGS and AN and between AN-PGS and ADHD were observed. These findings could guide future research in the development of new treatments that can mitigate the development of EDs among individuals with ADHD or ASD.

Aberrant functional gradient of thalamo-cortical circuitry in major depressive disorder and generalized anxiety disorder

BACKGROUND

Functional gradient analysis provides insights into the brain's macroscale organization; however, the differences in thalamo-cortical gradients between major depressive disorder (MDD) and generalized anxiety disorder (GAD) remain unclear. Investigating these heterogeneities may uncover disorder-specific neural mechanisms and enhance diagnostic precision, addressing the distinct yet overlapping features of these affective disorders.

METHODS

Resting-state functional MRI data were acquired from 88 healthy controls, 53 patients with MDD, and 28 patients with GAD. Functional gradient analysis was conducted to investigate differences in the spatial organization of the Thalamo-Cortical circuitry among three groups. The eccentricity index was computed to quantify the segregation of thalamic voxels in a two-dimensional gradient space.

RESULTS

Abnormal functional gradients in MDD and GAD were prrdominantly related to connectivity between the thalamus and the dorsal attention (DorsAttn) and somatomotor (SomMot) networks. Compared to HCs, both MDD and GAD patients showed decreased global eccentricity, with significant reductions observed only in the MDD group. Moreover, abnormal gradient organization significantly correlated with clinical symptoms and gene expressions in patient cohorts. In addition, using the eccentricity of Thalamo-Cortical circuitry as features, patients with MDD and GAD could be distinguished with over 72 % accuracy.

CONCLUSION

Our findings indicate significant alterations in the gradient organization of the Thalamo-DorsAttn and Thalamo-SomMot connectivity in these two patient populations, suggesting potential contributions to the etiology and diagnosis of MDD and GAD.

Biological pathways underlying the relationship between childhood maltreatment and Multimorbidity: A two-step, multivariable Mendelian randomisation study

Childhood maltreatment has been associated with multimorbidity of depression, coronary artery disease and type 2 diabetes. However, the biological mechanisms underlying this association remain unclear. We employed two-step and multivariable Mendelian randomisation (MR) to understand the role of three potential biological mediating mechanisms - inflammation (92 proteins), metabolic processes (54 markers), and cortisol - in the link between childhood maltreatment liability and multimorbidity. Using summary statistics from large-scale genome-wide association studies of European ancestry for childhood maltreatment (N = 185,414) and multimorbidity (Neffective = 156,717), we tested for the presence of an indirect effect via each mediator individually. We found a potential role of metabolic pathways. Up to 11% of the effect of childhood maltreatment on multimorbidity was mediated by triglycerides (indirect effect [95% CI]: 0.018 [0.009-0.027]), 8% by glycated haemoglobin (indirect effect: 0.013 [0.003-0.023]), and up to 7% by high-density lipoprotein cholesterol (indirect effect: 0.011 [0.005-0.017]). We did not find evidence for mediation via any inflammatory protein or cortisol. Our findings shed light on the biological mechanisms linking childhood maltreatment liability to multimorbidity, highlighting the role of metabolic pathways. Future studies may explore underlying pathways via non-biological mediators (e.g., lifestyle factors) or via multiple mediators simultaneously.

Characterizing Genetic-Predisposed Proteins Involving Insomnia by Integrating Genome-Wide Association Study Summary Statistics

Large case-control genome-wide association studies (GWASs) have detected loci associated with insomnia, but how these risk loci confer disease risk remains largely unknown. By integrating brain protein quantitative trait loci (pQTL) (NpQTL1 = 376, NpQTL2 = 152) and expression QTL (eQTL) (N = 452) datasets, with the latest insomnia GWAS summary statistics (Ncase = 109,548, NControls = 277440), we conducted proteome/transcriptome-wide association study (PWAS/TWAS) and Mendelian randomization (MR) analysis, aiming to identify causal proteins involving in the pathogenesis of insomnia. We also explored the bi-directional causality between insomnia and several common diseases. As a result, the altered protein level of 28 genes in the brain was associated with the risk of insomnia in the discovery stage of PWAS, of which 18 genes' associations were replicated in the confirmatory stage of PWAS. Among them, four proteins (2-aminoethanethiol dioxygenase (ADO), calcium-modulating cyclophilin ligand (CAMLG), islet cell autoantigen 1 like (ICA1L) and latexin (LXN)) were found to be the most likely causal genes for insomnia with validations from TWAS, MR, and colocalization results. Specifically, the higher protein level of ADO, CALMG, and ICA1L was causally associated with a lower risk of insomnia. In comparison, the higher protein level of LXN was causally associated with an increased risk for insomnia. Moreover, genetically predicted insomnia was causally associated with an increased risk of developing cardiovascular diseases and depression. In conclusion, our study identified ADO, CAMLG, ICA1L, and LXN as potentially causal proteins in the pathogenesis of insomnia. This could provide insights into further mechanistic studies and therapeutic development for insomnia.

Whole exome sequencing identified six novel genes for depressive symptoms

Previous genome-wide association studies of depression have primarily focused on common variants, limiting our comprehensive understanding of the genetic architecture. In contrast, whole-exome sequencing can capture rare coding variants, helping to explore the phenotypic consequences of altering protein-coding genes. Here, we conducted a large-scale exome-wide association study on 296,199 participants from the UK Biobank, assessing their depressive symptom scores through the Patient Health Questionnaire-4. We identified 22 genes associated with depressive symptoms, including 6 newly discovered genes (TRIM27, UBD, SVOP, ADGRB2, IRF2BPL, and ANKRD12). Both ontology enrichment analysis and plasma proteomics association analysis consistently revealed that the identified genes were associated with immune responses. Furthermore, we identified associations between these genes and brain regions related to depression, such as anterior cingulate cortex and orbitofrontal cortex. Additionally, phenome-wide association analysis demonstrated that TRIM27 and UBD were associated with neuropsychiatric, cognitive, biochemistry, and inflammatory traits. Our findings offer new insights into the potential mechanisms and genetic architecture of depressive symptoms.

The effect of fampridine on working memory: a randomized controlled trial based on a genome-guided repurposing approach

Working memory (WM), a key component of cognitive functions, is often impaired in psychiatric disorders such as schizophrenia. Through a genome-guided drug repurposing approach, we identified fampridine, a potassium channel blocker used to improve walking in multiple sclerosis, as a candidate for modulating WM. In a subsequent double-blind, randomized, placebo-controlled, crossover trial in 43 healthy young adults (ClinicalTrials.gov, NCT04652557), we assessed fampridine's impact on WM (3-back d-prime, primary outcome) after 3.5 days of repeated administration (10 mg twice daily). Independently of baseline cognitive performance, no significant main effect was observed (Wilcoxon P = 0.87, r = 0.026). However, lower baseline performance was associated with higher working memory performance after repeated intake of fampridine compared to placebo (rs = -0.37, P = 0.014, n = 43). Additionally, repeated intake of fampridine lowered resting motor threshold (F(1,37) = 5.31, P = 0.027, R2β = 0.01), the non-behavioral secondary outcome, indicating increased cortical excitability linked to cognitive function. Fampridine's capacity to enhance WM in low-performing individuals and to increase brain excitability points to its potential value for treating WM deficits.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Neuroscience in Pictures: 4. Depression

Major depressive disorder represents a complex heterogeneous syndrome with significant public health impact. This pictorial review explores the multifaceted pathophysiology of depression through the case of an individual suffering from depression. Genetic vulnerability and environmental etiological factors, including early life adversity, and their interactions create a biological diathesis through alterations in stress response systems and neural circuitry. We review current evidence for several interconnected pathophysiological mechanisms underlying depression, including monoamine neurotransmission, hypothalamic-pituitary-adrenal axis dysfunction, chronic inflammation, and reduced neuroplasticity. Using the Research Domain Criteria framework, we connect these mechanisms across multiple levels of analysis-from genes, circuits to behavior. Neuroimaging findings highlight disruptions in key networks including the default mode, salience, and executive control circuits. The effectiveness of pharmacological, psychotherapeutic and other non-pharmacological interventions in depression underscores the importance of targeting multiple biological systems. This review emphasizes depression's complex etiology involving dynamic interactions between genetic predisposition, environmental stressors, and neurobiological alterations, suggesting the need for personalized, multimodal therapeutic approaches.

Morbidity-bridging metabolic pathways: linking early cardiovascular disease risk and depression symptoms using a multi-modal approach

Aims

Prevalence of cardiovascular diseases (CVDs) and depression is rising globally. Their co-occurrence associates with poorer outcomes, potentially due to shared metabolic pathways. This study aimed to identify metabolic pathways linking depression symptoms and CVD risk factors.

Methods and results

Data from the Young Finns Study (YFS, n = 1,599, mean age 37 ± 5, 54% female) served as input for a network (mixed graphical models). Confirmatory analysis through covariate-adjusted regression was done with UK Biobank (UKB, n = 69,513, mean age 63 ± 7, 64% female). Mendelian randomization assessed causality using genome-wide association studies data. The study examined 52 plasma metabolites measured by nuclear magnetic resonance spectroscopy. Outcomes included depression symptoms (BDI in YFS, PHQ-9 in UKB) and CVD risk factors [systolic/diastolic blood pressure, carotid intima-media thickness (cIMT)]. Mendelian randomization inferred causal links between metabolites and depression or (intermediate markers of) CVD. Two bridge metabolites were identified: glucose linked to sleep pattern (P = 0.034); omega-3 fatty acids (FAs) linked to appetite change (P < 0.001); and both connected to cIMT (both P = 0.002). Mendelian randomization suggested glucose as causal in coronary artery disease (CAD) risk, while omega-3 FAs showed potential causal links to CAD, coronary artery calcification, and cIMT.

Conclusion

This study integrated three statistical techniques and identified two metabolic markers (glucose, omega-3 FAs) connecting depression and CVD on a symptom and risk factor level. The associations, established in a relatively young cohort, were replicated in a predominantly middle-aged cohort and emphasize both the generalizability of the findings across different populations and value of symptom-level analysis in depression and CVD comorbidity research.

Detection of positive selection on depression-associated genes

Although depression significantly impacts fitness, some hypotheses suggest that it may offer a survival benefit. However, there has been limited systematic investigation into the selection pressures acting on genes associated with depression at the genomic level. Here, we conducted comparative genomic analyses and computational molecular evolutionary analyses on 320 depression-associated genes at two levels, i.e., across the primate phylogeny (long timescale selection) and in modern human populations (recent selection). We identified seven genes under positive selection in the human lineage, and 46 genes under positive selection in modern human populations. Most positively selected variants in modern human populations were at UTR regions and non-coding exons, indicating the importance of gene expression regulation in the evolution of depression-associated genes. Positively selected genes are not only related to immune responses, but also function in reproduction and dietary adaptation. Notably, the proportion of depression-associated genes under positive selection was significantly higher than the positively selected genes at the genome-wide average level in African, East Asian, and South Asian populations. We also identified two positively selected loci that happened to be associated with depression in the South Asian population. Our study revealed that depression-associated genes are subject to varying selection pressures across different populations. We suggest that, in precision medicine-particularly in gene therapy-it is crucial to consider the specific functions of genes within distinct populations.

Blunted cortisol as a biomarker of depression based on the attenuation hypothesis: A Mendelian randomization analysis using depression as exposure

BACKGROUND

Both elevated and blunted cortisol responses have been associated with depression. Previous Mendelian randomization (MR) studies have largely ruled out cortisol as a cause of depression. Based on the attenuation hypothesis, this MR study used depression as exposure to assess whether cortisol might be a consequence and therefore a biomarker of depression.

METHODS

Strong (P < 5 × 10-8) and independent (r2 < 0.001) single nucleotide polymorphisms (SNPs) associated with broadly defined depression (294,322 cases, 741,438 controls) were used as instruments. These were applied to genetic associations with morning, fasting, and random plasma cortisol in the CORtisol NETwork (CORNET) consortium (n = 25,314), METabolic Syndrome in Men (METSIM) study (n = 6667), and Canadian Longitudinal Study on Aging (CLSA) cohort (n = 8299). Multivariable MR, adjusting for childhood maltreatment and major mental disorders, was conducted to address potential horizontal pleiotropy from dichotomous depression. Instruments were also selected by evidence of colocalization with major depressive disorder to address non-specificity.

RESULTS

Using 133 SNPs as instruments, depression was inversely associated with morning plasma cortisol (β per log-odds of genetic liability to depression = -0.107 [95 % CI, -0.181 to -0.032]) in the CORNET consortium. Replication in the METSIM study (β = -0.203 [95 % CI, -0.367 to -0.040]) and CLSA cohort (β = -0.091 [95 % CI, -0.220 to 0.039]) showed consistent but not always significant associations. Multivariable MR and follow-up analysis incorporating colocalization supported these findings.

CONCLUSIONS

Consistent with the attenuation hypothesis, blunted cortisol response appeared to be a consequence and potentially a biomarker of depression. Future studies are needed to provide more interpretable effect sizes and validate other biomarker measures.

Prefrontal ErbB4-positive interneurons for avoidance

Avoidance is a major behavior for survival. The prefrontal cortex (PFC) is known to be involved in approach-avoidance decision-making, but how PFC interneurons (INs) collaborate with excitatory neurons in this process remains unclear. Our research reveals that ErbB4+ interneurons (B4INs) increased calcium transients in avoidance behaviors of freely moving mice. B4IN inhibition or activation is required for and sufficient to induce avoidance behaviors. B4INs receive monosynaptic inputs from glutamatergic neurons in the basal forebrain (BF), whose activation and suppression induce and inhibit avoidance, respectively. By registering target neurons of B4INs, we show that most avoidance-associated neurons are under the inhibitory control of B4INs, suggesting that B4INs act by suppressing excitatory neurons to mediate avoidance behaviors. Finally, pharmacological inhibition of ErbB4 reduces avoidance behaviors, suggesting that B4IN activity depends on ErbB4 kinase activity. These results reveal a causal role for B4INs in avoidance behaviors.

Investigating causal relationships between gene expression and major depressive disorder via brain bulk-tissue and cell type-specific eQTL: A Mendelian randomization and Bayesian colocalization study

BACKGROUND

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder with complex genetic underpinnings. While genome-wide association studies (GWAS) have identified multiple risk loci, pinpointing causal genes within the human brain remains challenging, particularly given the regulatory complexity across different cell types.

METHODS

We performed summary data-based MR (SMR) and Bayesian colocalization analyses by integrating bulk-tissue eQTL data from 888 individuals with single-cell eQTL datasets from 192 donors representing major brain cell types (excitatory and inhibitory neurons, astrocytes, microglia, oligodendrocytes, OPCs/COPs, endothelial cells, and pericytes). GWAS summary statistics for MDD (170,756 cases and 329,443 controls) were used to assess the causal impact of gene expression. Sensitivity analyses, including the heterogeneity in dependent instruments (HEIDI) test and Steiger filtering, ensured robust inference.

RESULTS

In bulk tissue analyses, five genes (BTN3A2, SLC12A5, AREL1, GMPPB, and ZNF660) emerged as having robust causal evidence for MDD, displaying consistent MR signals and strong colocalization. Cell type-specific analyses revealed additional candidate genes in excitatory neurons (FLOT1, AL450423.1), astrocytes (AL121821.1), and oligodendrocytes (YLPM1, COP1).

CONCLUSION

Our integrative approach reveals that causal gene expression profiles differ markedly between bulk-tissue and specific brain cell types, emphasizing cellular heterogeneity in MDD pathogenesis and informing precision therapeutic strategies. These findings underscore the necessity of considering cell type-specific gene regulation when developing therapeutic interventions for MDD.

Large-scale transcriptomic analyses of major depressive disorder reveal convergent dysregulation of synaptic pathways in excitatory neurons

Major Depressive Disorder (MDD) is a common, complex disorder that is a leading cause of disability worldwide and a significant risk factor for suicide. In this study, we have performed the largest molecular analysis of MDD in postmortem human brains (846 samples across 458 individuals) in the subgenual Anterior Cingulate Cortex (sACC) and the Amygdala, two regions central to mood regulation and the pathophysiology of MDD. We found extensive expression differences, particularly at the level of specific transcripts, with prominent enrichment for genes associated with the vesicular functioning, the postsynaptic density, GTPase signaling, and gene splicing. We find associated transcriptional features in 107 of 243 genome-wide significant loci for MDD and, through integrative analyses, highlight convergence of genetic risk, gene expression, and network-based analyses on dysregulated glutamatergic signaling and synaptic vesicular functioning. Together, these results provide an initial mechanistic understanding of MDD and highlight potential targets for novel drug discovery.

Mediators of the association between education and periodontitis: Mendelian randomization study

AIM

To estimate the causal link between the risk of chronic periodontitis and educational attainment (EA).

METHODS

The biggest genome-wide association studies (GWAS) were used to conduct two-sample univariable Mendelian randomization (MR) analyses to evaluate the direct and combined effects of body mass index (BMI), smoking, household income, alcohol drinking, major depression, and EA on chronic periodontitis. To determine if putative mediators are causally involved in the pathway that mediates the relationship between EA and chronic periodontitis, a two-step MR analysis is performed.

RESULTS

MR evidence suggested a causal relationship between higher educational level and lower chronic periodontitis risk (OR: 0.72; 95% confidence interval (CI), 0.63 to 0.82; P < 0.001). The proportions mediated of the total effect of genetically predicted education on chronic periodontitis were 12.9%, 30.7%, 89.9%, 9.7%, and 16.4% for BMI, smoking, household income, alcohol drinking, and major depression, respectively.

CONCLUSION

The risk of chronic periodontitis is protected by higher EA. Obesity, smoking, income, alcohol drinking, major depression seem to be significant factors. Measures to alleviate the risk burden of chronic periodontitis caused by educational disparities may be achieved by addressing these factors.

The complex association of VRK2 with major depressive disorder in Han Chinese population

BACKGROUND

Major depressive disorder (MDD) is a polygenic condition with substantial heritability, with genome-wide association studies (GWAS) identifying several risk loci in European populations, including the VRK2 gene. However, the association between VRK2 and MDD in non-European populations, particularly in Han Chinese, remains underexplored.

METHODS

We genotyped four VRK2 SNPs (rs2678907, rs11682175, rs1568452, rs1518395) in a cohort of 1878 MDD cases and 1800 controls of Han Chinese descent. Genotyping was performed using SNaPShot, and linkage disequilibrium (LD) was assessed with SHEsis. Associations between the SNPs and MDD were evaluated via logistic regression in PLINK. VRK2 mRNA expression in the amygdala and peripheral blood was quantified by RT-qPCR, with statistical significance determined by ANCOVA and t-tests. A meta-analysis incorporating an independent East Asian GWAS cohort was also conducted.

RESULTS

In our Han Chinese cohort, rs2678907 was significantly associated with MDD (P = 4.17 × 10-5, OR = 1.217). Meta-analysis with independent East Asian GWAS further confirmed the associations of rs2678907 with MDD. Haplotype analysis of VRK2 SNPs in Han Chinese revealed the haplotypes (T-G for rs11682175-rs2678907 and C-G for rs1568452-rs2678907) associated with an increased MDD risk and elevated VRK2 mRNA expression. Additionally, MDD patients showed significantly higher VRK2 mRNA levels in peripheral blood than controls (P = 1.85 × 10-7).

CONCLUSIONS

These findings provide strong evidence for the role of VRK2 in MDD risk in Han Chinese individuals. Our results underscore the potential of VRK2 as a genetic and expression-based biomarker for MDD, highlighting the importance of accounting for population-specific genetic variations in psychiatric research. Further research is essential to explore the functional implications of VRK2 in MDD pathogenesis.

Identification of mitochondrial-related causal genes for major depression disorder via integrating multi-omics

CONTEXT

Mitochondria dysfunction plays a pivotal role in major depressive disorder (MDD), but the causal link between mitochondria dysfunction and MDD remains unclear.

AIMS

This study aimed to explore the causal effects of mitochondrial-related genes (MRGs) on MDD by integrating multi-omics data.

METHODS

Summary statistics of DNA methylation, gene expression, and protein for MRGs were obtained from the corresponding quantitative trait loci in European ancestry individuals. GWAS summary statistics for MDD were sourced from the Psychiatric Genomics Consortium (PGC, discovery) and FinnGen R10 study (replication). Summary-data-based Mendelian Randomization (SMR) was performed to assess the association between DNA methylation, gene expression, and protein abundances of MRGs with the risk of MDD. Colocalization analysis was employed to assess the potential shared genetic variants between MRGs and MDD. Two-sample MR was conducted to assess the sensitivity of the SMR results. Single-nucleus RNA-sequencing (snRNA-seq) and bulk RNA-seq data were used to explore the candidate MRG expression.

RESULTS

We identified methylation levels of PPTC7 (cg08752433) and methylation levels of VRS2 (cg07945879, cg14935711, cg00244776, cg15848685, cg12457901, cg16958594) associated with a decreased risk of MDD. Conversely, the methylation levels of VRS2 (cg26784891, cg05853013, cg04966294) and MRPL46 (cg00200755) were associated with increased risk of MDD. High expression of COQ8A and TRMT10C were associated with an increased risk of MDD. Notably, COQ8A was predominantly expressed in both inhibitory and excitatory neurons in MDD patients.

CONCLUSION

This study established a causal relationship between mitochondrial dysfunction and MDD, identifying candidate MRGs, and providing potential diagnostic and therapeutic targets for MDD.

Exon-variant interplay and multi-modal evidence identify endocrine dysregulation in severe psychiatric disorders impacting excitatory neurons

Bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia share genetic architecture, yet their molecular mechanisms remain elusive. Both common and rare genetic variants contribute to neural dysfunction, impacting cognition and behavior. This study investigates the molecular effects of genetic variants on human cortical single-cell types using a single-exon analysis approach. Integrating exon-level eQTLs (common variants influencing exon expression) and joint exon eQT-Scores (combining polygenic risk scores with exon-level gene expression) from a postmortem psychiatric cohort (BD = 15, MDD = 24, schizophrenia = 68, controls = 62) with schizophrenia-focused rare variant data from the SCHEMA consortium, we identified 110 core genes enriched in pathways including circadian entrainment (FDR = 0.02), cortisol synthesis and secretion (FDR = 0.026), and dopaminergic synapse (FDR = 0.038). Additional enriched pathways included hormone signaling (FDRs < 0.0298, including insulin, GnRH, aldosterone, and growth hormone pathways) and, notably, adrenergic signaling in cardiomyocytes (FDR = 0.0028). These pathways highlight shared molecular mechanisms in the three disorders. Single-nuclei RNA sequencing data from three cortical regions revealed that these core set genes are predominantly expressed in excitatory neuron layers 2-6 of the dorsolateral prefrontal cortex, linking molecular changes to cell types involved in cognitive dysfunction. Our results demonstrate the power of integrating multimodal genetic and transcriptomic data at the exon level. This approach moves beyond symptom-based diagnoses toward molecular classifications, identifying potential therapeutic targets for psychiatric disorders.

Transcriptional characteristics of human brain alterations in major depressive disorder: A systematic review

Many patients with major depressive disorder (MDD) experience limited treatment effectiveness due to an incomplete understanding of its neurobiological underpinnings. This review integrates neuroimaging and genetic data to examine structural and functional brain changes in MDD, alongside their genetic bases. A PRISMA-guided systematic review of imaging transcriptomics over the past decade was conducted using PubMed and Web of Science. Studies included MRI scans of both MDD patients and healthy controls, as well as brain-wide gene expression data, excluding those that were purely meta-analytical, lacked spatial correlations, or involved transdiagnostic analyses. Of the 206 studies reviewed, 20 met the inclusion criteria. Consistent patterns across studies reveal that key biological processes-such as synaptic signaling, calcium ion binding, neurodevelopment, immune regulation, and neurotransmitter transport-play a central role in brain alterations associated with MDD. Additionally, our findings suggest that electroconvulsive therapy (ECT) may alleviate symptoms by modulating these shared pathways. This review underscores the link between brain changes in MDD and specific gene expression profiles, offering insights that could inform more targeted therapeutic approaches.

Psychiatric factors predict type 2 diabetes mellitus in US Veterans

Co-occurrence of type 2 diabetes mellitus (T2D) and serious mental illnesses (SMI) is prevalent yet underappreciated, and significantly contributes to increased morbidity and reduced lifespan. There is, therefore, a need to identify T2D risk factors to inform preventative approaches to the care of SMI-diagnosed patients. Our objective was to use predictive modeling methods to capture risk factors for T2D in a sample of 618,203 Veterans using data obtained from hospital electronic health records (EHR). This case-control study assessed VISN4 Veterans with and without T2D diagnoses and SMI diagnoses (schizophrenia, SZ; schizoaffective, SZA; bipolar disorder, BD; major depression, MDD; 2009-2019). Demographic variables and medications were obtained from the EHR. Following rigorous data quality control, 543,979 Veterans qualified for analysis (Agemean[SD] = 65.9[17.6]years; body mass index(BMI)mean[SD] = 28.6[6.0]kg/m2; NT2D = 157,457[29%]; and Nmale = 506,257[93.1%]). Veterans with co-occurring SMI + T2D included NSZ = 2,087(36.5%), NSZA = 1,345(36.3%), NBD = 10,540(29.2%), and NMDD = 20,510(30%) compared to 112,973(28.6%) non-SMI controls (NSC) with T2D. Factors that predicted T2D (R2 = 34%) included age, sex, BMI, race/ethnicity, psychiatric diagnoses, and commonly prescribed psychiatric medications. Significant interactions were found between age (centered) and BMI on the odds of T2D (P < 0.001), as well as interaction between sex and BMI (P < 0.001), after adjusting for confounders. Veterans with SMI (SZ, MDD, SZA, and BD) had a higher likelihood of experiencing T2D, compared to the NSCs (ORSZ = 1.30, 95% CI = 1.21-1.40; ORMDD = 1.07, 95% CI = 1.05-1.10; ORSZA = 1.26, 95% CI = 1.16-1.38; ORBD = 1.05, 95% CI = 1.01-1.08). Finally, Veterans exposed to both selective serotonin reuptake inhibitor (SSRI) antidepressants and mood stabilizers had a 2.11 times increase in the odds of having T2D (95% CI = 2.06-2.16; P < 0.001) compared to Veterans not taking either medication. Four major psychiatric disorders (SZ, SZA, MDD, and BD) and several classes of medications used to treat them increased T2D risk. Our findings suggest that the measures assayed offer a potentially useful signal, that along with clinical, anthropometric, and biochemical measures can be used to ascertain metabolic risk. If confirmed with an independent sample, these findings could also inform medication choices made by prescribers.

Polygenic overlap between subjective well-being and psychiatric disorders and cross-ancestry validation

Subjective well-being (SWB) is important for understanding human behaviour and health. Although the connection between SWB and psychiatric disorders has been studied, common genetic mechanisms remain unclear. This study aimed to explore the genetic relationship between SWB and psychiatric disorders. Bivariate causal mixture modelling (MiXeR), polygenic risk score (PRS) and Mendelian randomization (MR) analyses showed substantial polygenic overlap and associations between SWB and the psychiatric disorders. Subsequent replication studies in East Asian populations confirmed the polygenic overlap between schizophrenia and SWB. The conditional and conjunctional false discovery rate analyses identified additional or shared genetic loci associated with SWB or psychiatric disorders. Functional annotation revealed enrichment of specific brain tissues and genes associated with SWB. The identified genetic loci showed cross-ancestry transferability between the European and Korean populations. Our findings provide valuable insights into the common genetic mechanisms underlying SWB and psychiatric disorders.

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

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

Alterations in fecal microbiota composition and cytokine expression profiles in adolescents with depression: a case-control study

Emerging evidence has highlighted that altered gut microbiota are associated with the onset and progression of depression via regulating the gut-brain axis. However, existing research has predominantly focused on children and adults, frequently neglecting adolescent depression. Given the rising prevalence and substantial impact of adolescent depression on functional impairment and suicidality, it is essential to focus more on this age group. In this study, we examined the fecal microbiota and inflammatory profiles of 99 depressed adolescents and 106 age-matched healthy controls using Illumina NovaSeq sequencing and multiplex immunoassays, respectively. Our findings revealed lower bacterial α-diversity and richness, alongside altered β-diversity in adolescents with depression. Gut dysbiosis associated with adolescent depression was characterized by increased pro-inflammatory genera such as Streptococcus and decreased anti-inflammatory genera like Faecalibacterium. These differential genera may serve as potential non-invasive biomarkers for adolescent depression, either individually or in combination. We also observed disruptions in the inferred microbiota functions in adolescent depression-associated microbiota, particularly in glycolysis and gluconeogenesis. Additionally, depressed adolescents exhibited systemic immune dysfunction, with elevated levels of pro-inflammatory cytokines and chemokines, which showed significant correlations with the differential genera. Our study bridges the gap between children and adults by providing new insights into the fecal microbiota characteristics and their links to immune system disruptions in depressed adolescents, which offer new targets for the diagnosis and treatment of depression in this age group.

Joint contribution of polygenic scores for depression and attention-deficit/hyperactivity disorder to youth suicidal ideation and attempt

Children presenting comorbid attention-deficit/hyperactivity disorder (ADHD) and depression symptoms have higher risks of later suicidal ideation and attempt. However, it is unclear to what extent this risk stems from individual differences in the genetic predisposition for ADHD and/or depression. We investigated the unique and combined contribution of genetic predisposition to ADHD and depression to suicidal ideation and attempt by early adulthood. Data were from two longitudinal population-based birth cohorts, the Quebec Longitudinal Study of Child Development and the Quebec Newborn Twin Study (total N = 1207). Genetic predisposition for ADHD and depression were measured using polygenic scores. Suicidal ideation and attempt by age 20 years were self-reported via questionnaires. Across the two cohorts, suicidal ideation and attempt were reported by 99 (8.2%) and 75 (6.1%) individuals, respectively. A higher polygenic score for depression was associated with significantly higher risk of suicidal ideation and attempt, while no significant associations were found for ADHD polygenic score. However, we found an interaction between polygenic scores for depression and ADHD in the association with suicide attempt (P = 0.012), but not suicidal ideation (P = 0.897). The association between polygenic score for depression and suicide attempt was significantly stronger for individuals with a higher polygenic score for ADHD. Individuals scoring ≥ 1-SD above the mean for both polygenic scores were at increased risk for suicide attempt compared to individuals with lower scores (OR 4.03, CI 1.64-9.90), as well as compared to individuals scoring ≥ 1-SD above the mean in only depression (OR 2.92, CI 1.01-8.50) or only ADHD (OR 4.88, CI 1.56-15.26) polygenic scores. Our findings suggest that genetic predisposition for ADHD and depression contributes to increase the risk of suicide attempt in a multiplicative, rather that additive, way. Our results contribute to our understanding of the etiology of suicide risk and may inform screening and risk stratification.

Genetic and neural mechanisms shared by schizophrenia and depression

Schizophrenia (SCZ) and depression are two prevalent mental disorders characterized by comorbidity and overlapping symptoms, yet the underlying genetic and neural mechanisms remain largely elusive. Here, we investigated the genetic variants and neuroimaging changes shared by SCZ and depression in Europeans and then extended our investigation to cross-ancestry (Europeans and East Asians) populations. Using conditional and conjunctional analyses, we found 213 genetic variants shared by SCZ and depression in Europeans, of which 82.6% were replicated in the cross-ancestry population. The shared risk variants exhibited a higher degree of deleteriousness than random and were enriched for synapse-related functions, among which fewer than 3% of shared variants showed horizontal pleiotropy between the two disorders. Mendelian randomization analyses indicated reciprocal causal effects between SCZ and depression. Using multiple trait genetic colocalization analyses, we pinpointed 13 volume phenotypes shared by SCZ and depression. Particularly noteworthy were the shared volume reductions in the left insula and planum polare, which were validated through large-scale meta-analyses of previous studies and independent neuroimaging datasets of first-episode drug-naïve patients. These findings suggest that the shared genetic risk variants, synapse dysfunction, and brain structural changes may underlie the comorbidity and symptom overlap between SCZ and depression.

Polygenic score analysis identifies distinct genetic risk profiles in Alzheimer's disease comorbidities

Alzheimer's disease (AD) is usually accompanied by comorbidities such as type 2 diabetes (T2D), epilepsy, major depressive disorder (MDD), and migraine headaches (MH) that can significantly affect patient management and progression. As AD, these comorbidities have their own cumulative common genetic risk component that can be explored in a single individual through polygenic scores. Utilizing data from the UK Biobank, we investigated the correlation between polygenic scores (PGS) for these comorbidities and their actual presentation in AD patients. We show that individuals with higher PGS values showed an elevated risk of developing T2D (OR 2.1, p = 1.07 × 10-11) and epilepsy (OR 1.5, p = 0.0176). High T2D-PGS is also associated with an earlier AD onset in individuals at high genetic risk for AD (AD-PGS). In contrast, no significant genetic associations were found for MDD and MH. Our findings show distinct common genetic risk factors for T2D and epilepsy carried by AD patients that are associated with increased prevalence and earlier disease onset. These results highlight the contribution of common genetic variation to the broader clinical landscape of AD and will contribute to future tailored patient management strategies for individuals at high genetic risk.

Association Between Educational Attainment and Chronic Pain: A Mediation Mendelian Randomization Study

Background

The underlying association between educational attainment (EA) and chronic pain (CP) risk is not clear. This study aimed to investigate the causal relationship of EA with CP using Mendelian randomization (MR).

Methods

Single nucleotide polymorphisms (SNPs) for EA were selected from the Social Science Genetic Association Consortium (SSGAC). Inverse-variance weighted (IVW), weighted median, penalized weighted median, maximum likelihood (ML), and MR-Egger methods were used to estimate causal effects. Two sample MR analyses were undertaken to assess whether EA has a causal effect on CP. We also performed mediation analyses to estimate the mediation effects.

Results

A genetically predicted higher EA was associated with a decreased risk of multisite chronic pain (MCP) (odds ratio [OR] = 0.772, 95% confidence interval [CI] 0.732-0.816 per one standard deviation of longer education, P < 0.05), and the Genome-wide association studies (GWAS) data for chronic widespread pain (CWP) supported the result mentioned above. Potential mediators included body mass index (BMI) (OR = 1.176, 95% CI 1.091-1.267, P < 0.05), smoking (OR = 1.054, 95% CI 1.028-1.081, P < 0.05), and depression (OR = 1.201, 95% CI 1.147-1.258, P < 0.05) have all been proven to be causally associated with MCP. The proportions of the effects of genetically predicted EA mediated through genetically predicted BMI, smoking, and depression were 17.1%, 23.6%, and 9.2%, respectively.

Conclusion

Genetically predicted higher educational attainment reduces multisite chronic pain risk, partially mediated by body mass index (17.1%), smoking (23.6%), and depression (9.2%), highlighting education's protective role and its potential in chronic pain prevention strategies.

The independent role of fine particulate matter and genetic liability on cognition in older adults

BACKGROUND

Genetic susceptibility to mental health and cognitive traits, as well as air pollution, significantly impact cognition. The interplay between polygenic liability and fine particulate matter (PM2.5) remains unclear due to the limited number of large-scale studies in Asia. This study utilized the Taiwan Biobank, a nationwide community-based database, to investigate the main and modified effect of PM2.5 on individuals' polygenic susceptibility in cognition.

METHODS

Polygenic risk score (PRS) for cognitive performance (CP PRS), Alzheimer's disease (AD PRS), schizophrenia (SCZ PRS), and major depression (MDD PRS) were computed representing genetic susceptibility for an individual. APOE genotype was classified into E3/E3, E3/E4, and E4/E4. The five-year average concentration of PM2.5 from satellite images was used for defining environmental exposure. Cognitive performance was evaluated via the Mini-Mental State Examination (MMSE) score. The association between personal genetic susceptibility, PM2.5, and cognitive performance was examined using multilevel linear regression with the adjustment of age, sex, batch effect, and population stratification effect. The gene-environment synergism was examined with the inclusion of product term of PM2.5 and PRS in the multivariate model.

RESULTS

Our analyses included 25,593 participants from 164 townships. Participants exposed to higher PM2.5 concentrations had a lower MMSE score (Beta=-0.0830 corresponding to a 1 µg/m3 increase in PM2.5 concentration, 95% CI, -0.0973 to -0.0688, p-value < 0.0001). After controlling for PM2.5 concentration, CP PRS (Beta = 0.1729, 95% CI, 0.1470 to 0.1988, p-value < 0.0001), SCZ PRS (Beta=-0.0632, 95% CI, -0.0891 to -0.0374, p-value < 0.0001), and AD PRS (Beta=-0.0321, 95% CI, -0.0580 to -0.0062, p-value = 0.0153) were associated with MMSE score. After further examination of gene-environment synergism, no interaction effect was identified, indicating different mechanism of PM2.5 and genetic liability to influence cognitive performance.

CONCLUSIONS

Human polygenic loading and PM2.5 may impact cognition via an independent pathway. A prevention strategy targeting air pollution reduction may effectively improve the cognitive performance. Multiple exposures and their influences on the long-term change of cognition were required in future research.

Genetic causal effects of multi-site chronic pain on post-traumatic stress disorder: Evidence from a two-sample, two-step Mendelian randomization study

BACKGROUND

Existing evidence supports a correlation between multi-site chronic pain and post-traumatic stress disorder (PTSD), but it is yet to be determined if this correlation is causal and in what direction the causation works.

METHODS

Applying two-sample Mendelian randomization (MR) analysis to data from available genome-wide association studies in populations of European ancestry, we estimated the causal association between multi-site chronic pain and no pain versus PTSD. Moreover, we used multivariable and mediation MR analysis to assess the mediating effects of 13 lifestyle factors or diseases on the causal relationship between multi-site chronic pain and PTSD. The MR analyses were mainly conducted with the inverse variance weighted (IVW) method, followed by various sensitivity and validation analyses.

RESULTS

Multi-site chronic pain dramatically increases the risk of developing PTSD (odds ratio [OR]IVW = 2.39, 95 % confidence interval [CI] = 1.72-3.31, p = 2.10 × 10-7), and no pain significantly reduces the risk of developing PTSD (ORIVW = 0.12, 95 % CI = 0.05-0.30, p = 3.14 × 10-6). Multivariable MR found that 13 potential confounding factors do not influence the causal effect of multi-site chronic pain on PTSD. Moreover, body mass index (BMI) (6.98 %), educational attainment (8.79 %), major depressive disorder (MDD) (36.98 %) and insomnia (27.25 %) mediate the causal connection between multi-site chronic pain and PTSD.

CONCLUSION

Overall, individuals with multi-site chronic pain may be at a higher risk of developing PTSD, and this risk is partially influenced by the pathways involving BMI, educational attainment, MDD, and insomnia. These factors offer potential targets for therapeutic interventions.

Psychiatric genetics in the diverse landscape of Latin American populations

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

Cross-ancestry genome-wide association study and systems-level integrative analyses implicate new risk genes and therapeutic targets for depression

Deciphering the genetic architecture of depression is pivotal for characterizing the associated pathophysiological processes and development of new therapeutics. Here we conducted a cross-ancestry genome-wide meta-analysis on depression (416,437 cases and 1,308,758 controls) and identified 287 risk loci, of which 49 are new. Variant-level fine mapping prioritized potential causal variants and functional genomic analysis identified variants that regulate the binding of transcription factors. We validated that 80% of the identified functional variants are regulatory variants, and expression quantitative trait loci analysis uncovered the potential target genes regulated by the prioritized risk variants. Gene-level analysis, including transcriptome and proteome-wide association studies, colocalization and Mendelian randomization-based analyses, prioritized potential causal genes and drug targets. Gene prioritization analyses highlighted likely causal genes, including TMEM106B, CTNND1, AREL1 and so on. Pathway analysis indicated significant enrichment of depression risk genes in synapse-related pathways. Finally, knockdown of Tmem106b in mice resulted in depression-like behaviours, supporting the involvement of Tmem106b in depression. Our study identified new risk loci, likely causal variants and genes for depression, providing important insights into the genetic architecture of depression and potential therapeutic targets.

Genetic correlation, pleiotropic loci and shared risk genes between major depressive disorder and gastrointestinal tract disorders

BACKGROUND

Major depressive disorder (MDD) is associated with gastrointestinal tract (GIT) disorders, while genetic correlation, pleiotropic loci and shared risk genes remain to be explored.

METHODS

Leveraging genome-wide association study statistics for MDD (n = 170,756), peptic ulcer disease (PUD; n = 16,666), gastroesophageal reflux disease (GORD; n = 54,854), PUD and/or GORD and/or medications (PGM; n = 90,175), irritable bowel syndrome (IBS; n = 28,518), and inflammatory bowel disease (IBD; n = 7045), we determined global and local genetic correlations, identified pleiotropic loci, performed gene-level evaluations, and inferred causal associations using bidirectional Mendelian randomization.

RESULTS

We found global correlation of MDD with PUD (rg = 0.444, P = 3.135 × 10-24), GORD (rg = 0.459, P = 2.568 × 10-65), PGM (rg = 0.498, P = 6.094 × 10-114), IBS (rg = 0.621, P = 2.483 × 10-63), and IBD (rg = 0.171, P = 1.824 × 10-5). We identified 12 locally correlated regions between MDD and GIT disorders except for IBD, and one shared region (chr11:111985737-113,103,996) for PGM, GORD, and IBS. We found one pleiotropic locus for PUD, 12 for GORD, 30 for PGM, eight for IBS, and seven for IBD, and five shared loci (rs138786869, rs2284189, rs3130063, rs35789010, rs7568369) for GORD and PGM. We respectively observed 14 and 20 overlapping genes for MDD-GORD and MDD-PGM. We showed genetic liabilities to GORD, PGM, and IBS causally increase MDD risk, while all reverse causalities are significant.

CONCLUSIONS

Our work identifies genetic architectures shared between MDD and GIT disorders, contributes genetic insights to understand depression in the context of gut-brain interactions, and provides potential targets to treat gastrointestinal symptoms in depressive patients.

Identifying novel chemical-related susceptibility genes for five psychiatric disorders through integrating genome-wide association study and tissue-specific 3'aQTL annotation datasets

The establishment of 3'aQTLs comprehensive database provides an opportunity to help explore the functional interpretation from the genome-wide association study (GWAS) data of psychiatric disorders. In this study, we aim to search novel susceptibility genes, pathways, and related chemicals of five psychiatric disorders via GWAS and 3'aQTLs datasets. The GWAS datasets of five psychiatric disorders were collected from the open platform of Psychiatric Genomics Consortium (PGC, https://www.med.unc.edu/pgc/ ) and iPSYCH ( https://ipsych.dk/ ) (Demontis et al. in Nat Genet 51(1):63-75, 2019; Grove et al. in Nat Genet 51:431-444, 2019; Genomic Dissection of Bipolar Disorder and Schizophrenia in Cell 173: 1705-1715.e1716, 2018; Mullins et al. in Nat Genet 53: 817-829; Howard et al. in Nat Neurosci 22: 343-352, 2019). The 3'untranslated region (3'UTR) alternative polyadenylation (APA) quantitative trait loci (3'aQTLs) summary datasets of 12 brain regions were obtained from another public platform ( https://wlcb.oit.uci.edu/3aQTLatlas/ ) (Cui et al. in Nucleic Acids Res 50: D39-D45, 2022). First, we aligned the GWAS-associated SNPs of psychiatric disorders and datasets of 3'aQTLs, and then, the GWAS-associated 3'aQTLs were identified from the overlap. Second, gene ontology (GO) and pathway analysis was applied to investigate the potential biological functions of matching genes based on the methods provided by MAGMA. Finally, chemical-related gene-set analysis (GSA) was also conducted by MAGMA to explore the potential interaction of GWAS-associated 3'aQTLs and multiple chemicals in the mechanism of psychiatric disorders. A number of susceptibility genes with 3'aQTLs were found to be associated with psychiatric disorders and some of them had brain-region specificity. For schizophrenia (SCZ), HLA-A showed associated with psychiatric disorders in all 12 brain regions, such as cerebellar hemisphere (P = 1.58 × 10-36) and cortex (P = 1.58 × 10-36). GO and pathway analysis identified several associated pathways, such as Phenylpropanoid Metabolic Process (GO:0009698, P = 6.24 × 10-7 for SCZ). Chemical-related GSA detected several chemical-related gene sets associated with psychiatric disorders. For example, gene sets of Ferulic Acid (P = 6.24 × 10-7), Morin (P = 4.47 × 10-2) and Vanillic Acid (P = 6.24 × 10-7) were found to be associated with SCZ. By integrating the functional information from 3'aQTLs, we identified several susceptibility genes and associated pathways especially chemical-related gene sets for five psychiatric disorders. Our results provided new insights to understand the etiology and mechanism of psychiatric disorders.

The causal relationship of inflammation-related factors with osteoporosis: A Mendelian Randomization Analysis

BACKGROUND

We used Mendelian randomization (MR) approach to examine whether genetically determined inflammation-related risk factors play a role in the onset of osteoporosis (OP) in the European population.

METHODS

Genome-wide association studies (GWASs) summary statistics of estimated bone mineral density (eBMD) obtained from the public database GEnetic Factors for OSteoporosis Consortium (GEFOS) including 142,487 European people. For exposures, we utilized GWAS data of 9 risk factors including diseases chronic kidney disease (CKD) (41,395 cases and 439,303 controls), type 2 diabetes (T2D) (88,427 cases and 566,778 controls), Alzheimer's disease (AD) (71,880 cases, 383,378 controls) and major depression disorder (MDD) (9240 cases and 9519 controls) and lifestyle behaviors are from different consortiums. Inverse variance weighted (IVW) analysis was principal method in this study and random effect model was applied; MR-Egger method and weighted median method were also performed for reliable results. Cochran's Q test and MR-Egger regression were used to detect heterogeneity and pleiotropy and leave-one-out analysis was performed to find out whether there are influential SNPs.

RESULTS

We found that T2D (IVW: β = 0.05, P = 0.0014), FI (IVW: β = -0.22, P < 0.001), CKD (IVW: β = 0.02, P = 0.009), ALZ (IVW: β = 0.06, P = 0.005), Coffee consumption (IVW: β = 0.11, P = 0.003) were causally associated with OP (P<0.006after Bonferroni correction).

CONCLUSIONS

Our study revealed that T2D, FI, CKD, ALZ and coffee consumption are causally associated with OP. Future interventions targeting factors above could provide new clinical strategies for the personalized prevention and treatment of osteoporosis.