Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions.
paper
Cited
Public
- Authors
- Howard, David M; Adams, Mark J; Clarke, Toni-Kim; Hafferty, Jonathan D; Gibson, Jude; Shirali, Masoud; Coleman, Jonathan R I; Hagenaars, Saskia P; Ward, Joey; Wigmore, Eleanor M; Alloza, Clara; Shen, Xueyi; Barbu, Miruna C; Xu, Eileen Y; Whalley, Heather C; Marioni, Riccardo E; Porteous, David J; Davies, Gail; Deary, Ian J; Hemani, Gibran; Berger, Klaus; Teismann, Henning; Rawal, Rajesh; Arolt, Volker; Baune, Bernhard T; Dannlowski, Udo; Domschke, Katharina; Tian, Chao; Hinds, David A; 23andMe Research Team; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium; Trzaskowski, Maciej; Byrne, Enda M; Ripke, Stephan; Smith, Daniel J; Sullivan, Patrick F; Wray, Naomi R; Breen, Gerome; Lewis, Cathryn M; McIntosh, Andrew M
- Year
- 2019
- Journal
- Nature neuroscience
- PMID
- 30718901
- DOI
- 10.1038/s41593-018-0326-7
- PMCID
- PMC6522363
Major depression is a debilitating psychiatric illness that is typically associated with low mood and anhedonia. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximize sample size, we meta-analyzed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 genesets associated with depression, including both genes and gene pathways associated with synaptic structure and neurotransmission. An enrichment analysis provided further evidence of the importance of prefrontal brain regions. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant after multiple testing correction. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding etiology and developing new treatment approaches.
(A) Manhattan plot of the observed –log10 P-values of each variant for an association with depression in the meta-analysis (n = 807,553; 246,363 cases and 561,190 controls). Variants are positioned according to the GRCh37 assembly
(A) Significance of cell type enrichment using a partitioned heritability approach. The dashed line represents statistical significance after Bonferroni correction (-log10P = 2.36) and * indicates significant enrichment for that cell type(B) Significance of enrichment estimates, based on genetic summary statistics, for brain regions using GTEx. The dashed line represents the Bonferroni cut-off for statistical significance (-log10P = 2.41) and * indicates significant enrichment for that brain region(C) Significant enrichment P-values, based on genetic summary statistics, for brain cell regions using GTEx overlaid on a physical representation of brain anatomyThe pseudo-coloring used in Figure 2C highlights the P-values of the regions of the brain in red that were significantly enriched (P < 0.05) for depression variants
Chord diagram of genes significantly associated (P < 2.80 × 10-6) with depression and the second level Anatomical Therapeutic Chemical classifications to which interacting drugs have been assigned. The width of each line is determined by the number of drugs known to interact with each gene. The genes are ordered by significance with depression with those most significantly associated located at the top of the diagramThe second level Anatomical Therapeutic Chemical classifications identified were: Stomatological preparations (A01), Drugs for acid related disorders (A02), Drugs for functional gastrointestinal disorders (A03), Bile and liver therapy (A05), Drugs for constipation (A06), Drugs used in diabetes (A10), Vitamins (A11), Mineral Supplements (A12), Anabolic agents for systemic use (A14), Blood substitutes and perfusion solutions (B05), Other hematological agents (B06), Cardiac therapy (C01), Diuretics (C03), Peripheral vasodilators (C04), Vasoprotectives (C05), Beta blocking agents (C07), Calcium channel blockers (C08), Corticosteroids, dermatological preparations (D07), Anti-acne preparations (D10), Other dermatological preparations (D11), Other gynecologicals (G02), Sex hormones and modulators of the genital system (G03), Urologicals (G04), Pituitary and hypothalamic hormones and analogues (H01), Corticosteroids for systemic use (H02), Antibacterials for systemic use (J01), Antivirals for systemic use (J05), Vaccines (J07), Antineoplastic agents (L01), Endocrine therapy (L02), Immunostimulants (L03), Immunosuppressants (L04), Anti-inflammatory and antirheumatic products (M01), Muscle relaxants (M03), Antigout preparations (M04), Drugs for treatment of bone diseases (M05), Anesthetics (N01), Analgesics (N02), Antiepileptics (N03), Anti-Parkinson drugs (N04), Psycholeptics (N05), Psychoanaleptics (N06), Other nervous system drugs (N07), Antiprotozoals (P01), Ectoparasiticides, incl. scabicides, insecticides and repellents (P03), Nasal preparations (R01), Drugs for obstructive airway diseases (R03), Antihistamines for systemic use (R06), Ophthalmologicals (S01), Otologicals (S02), Ophthalmological and otological preparations (S03), All other therapeutic products (V03), Diagnostic agents (V04), and Diagnostic radiopharmaceuticals (V09)
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| The role of co-occurring conditions and genetics in the associations of eating disorders with attention-deficit/hyperactivity disorder and autism spectrum disorder. | Christiansen GB et al. | — | 2025 | → |
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| Unraveling the Genetic Link Between Endocrine Hormones and Psychiatric Disorders: An Atlas of Genetic Correlations. | Li JL | — | 2025 | → |
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| Acute Stress Increases Striatal Connectivity With Cortical Regions Enriched for μ and κ Opioid Receptors. | Zhukovsky P et al. | — | 2024 | → |
| A depression-related lncRNA signature predicts the clinical outcome and immune characteristics of gastric cancer. | Ning B et al. | — | 2024 | → |
| A Developmentally-Informative Genome-wide Association Study of Alcohol Use Frequency. | Thomas NS et al. | — | 2024 | → |
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| A Genetic Analysis of Current Medication Use in the UK Biobank. | Rohde PD | — | 2024 | → |
| A genome-wide association study identifies candidate genes for sleep disturbances in depressed individuals. | Yang X et al. | — | 2024 | → |
| A Glucocorticoid-Sensitive Hippocampal Gene Network Moderates the Impact of Early-Life Adversity on Mental Health Outcomes. | Arcego DM et al. | — | 2024 | → |
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| A Metabolome-Wide Mendelian Randomization Study Identifies Dysregulated Arachidonic Acid Synthesis as a Potential Causal Risk Factor for Bipolar Disorder. | Stacey D et al. | — | 2024 | → |
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| Breaking down causes, consequences, and mediating effects of telomere length variation on human health. | Moix S et al. | — | 2024 | → |
| Bridging Three Years of Insights: Examining the Association Between Depression and Gallstone Disease. | Wang HZ et al. | — | 2024 | → |
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| Evidence for strong genetic correlations among internalizing psychopathology and related self-reported measures using both genomic and twin/adoptive approaches. | Gustavson DE et al. | — | 2024 | → |
| Examining Differences in the Genetic and Functional Architecture of Attention-Deficit/Hyperactivity Disorder Diagnosed in Childhood and Adulthood. | Breunig S et al. | — | 2024 | → |
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| Exploring genetic risk for catatonia in a genome wide association study and polygenic risk score analysis. | Wilson JE et al. | — | 2024 | → |
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| Familial coaggregation and shared genetic influence between major depressive disorder and gynecological diseases. | Chen CY et al. | — | 2024 | → |
| Family-based genetic analysis in schizophrenia by whole-exome sequence to identify rare pathogenic variants. | Shang B et al. | — | 2024 | → |
| Female genital prolapse and risk of psychiatric disorders: A two-sample Mendelian randomization analysis. | Zhou Q et al. | — | 2024 | → |
| Fibroblasts as an in vitro model of circadian genetic and genomic studies. | Francia M et al. | — | 2024 | → |
| Frailty and psychiatric disorders: A bidirectional Mendelian randomization study. | Chen JH et al. | — | 2024 | → |
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| Ganoderic acid A ameliorates depressive-like behaviors in CSDS mice: Insights from proteomic profiling and molecular mechanisms. | Xu JJ et al. | — | 2024 | → |
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| Genetically predicted fatty liver disease and risk of psychiatric disorders: A mendelian randomization study. | Xu WM et al. | — | 2024 | → |
| Genetically predicted high serum sex hormone-binding globulin levels are associated with lower ischemic stroke risk: A sex-stratified Mendelian randomization study. | Sun W et al. | — | 2024 | → |
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| Genetic estimation of causalities between educational attainment with common digestive tract diseases and the mediating pathways. | Wang Y et al. | — | 2024 | → |
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| Genetic Risk For Depression and Quality of Life in Patients With Head and Neck Cancer. | Henry M et al. | — | 2024 | → |
| Genetic risk for hospitalization of African American patients with severe mental illness reveals HLA loci. | Lori A et al. | — | 2024 | → |
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| Genome-wide association study implicates the role of TBXAS1 in the pathogenesis of depressive symptoms among the Korean population. | Park K et al. | — | 2024 | → |
| Genome-wide association study of early-onset and late-onset postpartum depression: the IGEDEPP prospective study. | Tebeka S et al. | — | 2024 | → |
| Genome-Wide Association Study of Obsessive-Compulsive Symptoms including 33,943 individuals from the general population. | Strom NI et al. | — | 2024 | → |
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| Genome-wide meta-analysis of ascertainment and symptom structures of major depression in case-enriched and community cohorts. | Adams MJ et al. | — | 2024 | → |
| Genome-Wide Polygenic Score for Muscle Strength Predicts Risk for Common Diseases and Lifespan: A Prospective Cohort Study. | Herranen P et al. | — | 2024 | → |
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| Genetic variations in the retrograde endocannabinoid signaling pathway in Chinese patients with major depressive disorder. | Xu H et al. | — | 2023 | → |
| Genome-wide analyses reveal novel opioid use disorder loci and genetic overlap with schizophrenia, bipolar disorder, and major depression. | Holen B et al. | — | 2023 | → |
| Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration. | Austin-Zimmerman I et al. | — | 2023 | → |
| Genome-wide association study of antisocial personality disorder diagnostic criteria provides evidence for shared risk factors across disorders. | Li W et al. | — | 2023 | → |
| Genome-wide multi-trait analysis of irritable bowel syndrome and related mental conditions identifies 38 new independent variants. | Alemany S et al. | — | 2023 | → |
| Glycoprotein acetyls and depression: Testing for directionality and potential causality using longitudinal data and Mendelian randomization analyses. | Crick DCP et al. | — | 2023 | → |
| GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors. | Docherty AR et al. | — | 2023 | → |
| High genetic risk for depression as an independent risk factor for mortality in patients referred for coronary angiography. | Krämer RM et al. | — | 2023 | → |
| High-throughput screening of glucocorticoid-induced enhancer activity reveals mechanisms of stress-related psychiatric disorders. | Penner-Goeke S et al. | — | 2023 | → |
| Hofbauer cell function in the term placenta associates with adult cardiovascular and depressive outcomes. | Fitzgerald E et al. | — | 2023 | → |
| Identification of four novel loci associated with psychotropic drug-induced weight gain in a Swiss psychiatric longitudinal study: A GWAS analysis. | Sjaarda J et al. | — | 2023 | → |
| Identification of region-specific splicing QTLs in human hippocampal tissue and its distinctive role in brain disorders. | Li X et al. | — | 2023 | → |
| Identifying causal associations between early sexual intercourse or number of sexual partners and major depressive disorders: A bidirectional two-sample Mendelian randomization analysis. | Lu Z et al. | — | 2023 | → |
| Identifying potential risk genes and pathways for neuropsychiatric and substance use disorders using intermediate molecular mediator information. | Gedik H et al. | — | 2023 | → |
| Immune System and Brain/Intestinal Barrier Functions in Psychiatric Diseases: Is Sphingosine-1-Phosphate at the Helm? | Martín-Hernández D et al. | — | 2023 | → |
| Impact of selection bias on polygenic risk score estimates in healthcare settings. | Lee YH et al. | — | 2023 | → |
| Inferring cell-type-specific causal gene regulatory networks during human neurogenesis. | Aygün N et al. | — | 2023 | → |
| Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings. | Hicks EM et al. | — | 2023 | → |
| Interplay of Metabolome and Gut Microbiome in Individuals With Major Depressive Disorder vs Control Individuals. | Amin N et al. | — | 2023 | → |
| Investigating the relationship between depression and breast cancer: observational and genetic analyses. | Wu X et al. | — | 2023 | → |
| Investigating the role of the relaxin-3/RXFP3 system in neuropsychiatric disorders and metabolic phenotypes: A candidate gene approach. | Wong WLE et al. | — | 2023 | → |
| Isoform-level transcriptome-wide association uncovers genetic risk mechanisms for neuropsychiatric disorders in the human brain. | Bhattacharya A et al. | — | 2023 | → |
| Leveraging genetic overlap between irritability and psychiatric disorders to identify genetic variants of major psychiatric disorders. | Jung K et al. | — | 2023 | → |
| Linking neuropsychiatric disease to neuronal metabolism. | Schmidt MV | — | 2023 | → |
| Local genetic correlations exist among neurodegenerative and neuropsychiatric diseases. | Reynolds RH et al. | — | 2023 | → |
| Major depression disorder may causally associate with the increased atrial fibrillation risk: evidence from two-sample mendelian randomization analyses. | Wang L et al. | — | 2023 | → |
| Major depressive disorder. | Marx W et al. | — | 2023 | → |
| Major depressive disorder and chronic gastritis: A bidirectional two-sample Mendelian randomization study. | Li J et al. | — | 2023 | → |
| Major depressive disorder plays a vital role in the pathway from gastroesophageal reflux disease to chronic obstructive pulmonary disease: a Mendelian randomization study. | Zou M et al. | — | 2023 | → |
| Mapping microRNA expression quantitative trait loci in the prenatal human brain implicates miR-1908-5p expression in bipolar disorder and other brain-related traits. | Toste CC et al. | — | 2023 | → |
| Mendelian randomization analyses identify bidirectional causal relationships of obesity with psychiatric disorders. | Chen W et al. | — | 2023 | → |
| Mendelian randomization shows depression increases the risk of type 2 diabetes. | Jin H et al. | — | 2023 | → |
| Mendelian Randomization Using the Druggable Genome Reveals Genetically Supported Drug Targets for Psychiatric Disorders. | Li X et al. | — | 2023 | → |
| Meta-Analyses of Genome-Wide Association Studies for Postpartum Depression. | Guintivano J et al. | — | 2023 | → |
| Methylome-wide association study of anxiety disorders. | Hettema JM et al. | — | 2023 | → |
| Multimodal Data Integration Advances Longitudinal Prediction of the Naturalistic Course of Depression and Reveals a Multimodal Signature of Remission During 2-Year Follow-up. | Habets PC et al. | — | 2023 | → |
| Multi-PGS enhances polygenic prediction by combining 937 polygenic scores. | Albiñana C et al. | — | 2023 | → |
| Multiple genes in a single GWAS risk locus synergistically mediate aberrant synaptic development and function in human neurons. | Zhang S et al. | — | 2023 | → |
| Multiple psychiatric polygenic risk scores predict associations between childhood adversity and bipolar disorder. | Yao K et al. | — | 2023 | → |
| Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program. | Cheng Y et al. | — | 2023 | → |
| Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning. | Neumann A et al. | — | 2023 | → |
| Neurobiological mechanisms of ECT and TMS treatment in depression: study protocol of a multimodal magnetic resonance investigation. | Frid LM et al. | — | 2023 | → |
| Nomogram model for predicting the risk of post-stroke depression based on clinical characteristics and DNA methylation. | Luo S et al. | — | 2023 | → |
| Novel synergistic treatment for depression: involvement of GSK3β-regulated AMPA receptors in the prefrontal cortex of mice. | Guo L et al. | — | 2023 | → |
| Obesity as a causal risk factor for depression: Systematic review and meta-analysis of Mendelian Randomization studies and implications for population mental health. | Jokela M et al. | — | 2023 | → |
| Objective and subjective measures of sleep initiation are differentially associated with DNA methylation in adolescents. | Larsen M et al. | — | 2023 | → |
| Occupational factors and low back pain: a Mendelian randomization study. | Wang Z et al. | — | 2023 | → |
| Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder. | Dahl A et al. | — | 2023 | → |
| Phosphodiesterase and psychiatric disorders: a two-sample Mendelian randomization study. | Jiang M et al. | — | 2023 | → |
| Polygenicity of Comorbid Depression in Multiple Sclerosis. | Kowalec K et al. | — | 2023 | → |
| Polygenic liabilities underlying job stress and exhaustion over a 10-year follow-up: A general population study. | Saarinen A et al. | — | 2023 | → |
| Polygenic regression uncovers trait-relevant cellular contexts through pathway activation transformation of single-cell RNA sequencing data. | Ma Y et al. | — | 2023 | → |
| Polygenic risk prediction: why and when out-of-sample prediction R<sup>2</sup> can exceed SNP-based heritability. | Wang X et al. | — | 2023 | → |
| Polygenic risk scores of lithium response and treatment resistance in major depressive disorder. | Xiong Y et al. | — | 2023 | → |
| Potential Causal Association between Depression and Oral Diseases: A Mendelian Randomization Study. | Zhang X et al. | — | 2023 | → |
| Predicting outcomes at the individual patient level: what is the best method? | Liu Q et al. | — | 2023 | → |
| Preliminary Evidence for Genetic Nurture in Depression and Neuroticism Through Polygenic Scores. | Tubbs JD et al. | — | 2023 | → |
| Proteome-wide Mendelian randomization reveals the causal effects of immune-related plasma proteins on psychiatric disorders. | Dang X et al. | — | 2023 | → |
| Psychiatric polygenic risk as a predictor of COVID-19 risk and severity: insight into the genetic overlap between schizophrenia and COVID-19. | Alemany-Navarro M et al. | — | 2023 | → |
| Psychological, endocrine and polygenic predictors of emotional well-being during the COVID-19 pandemic in a longitudinal birth cohort. | Nguyen T et al. | — | 2023 | → |
| Reduced Vrk2 expression is associated with higher risk of depression in humans and mediates depressive-like behaviors in mice. | Yin MY et al. | — | 2023 | → |
| Relationship Between the Ovarian Cyst and Depression: A Two-Sample Mendelian Randomization Study. | Wen J et al. | — | 2023 | → |
| Robustness of quantifying mediating effects of genetically regulated expression on complex traits with mediated expression score regression. | Lin C et al. | — | 2023 | → |
| Schizophrenia-associated NRXN1 deletions induce developmental-timing- and cell-type-specific vulnerabilities in human brain organoids. | Sebastian R et al. | — | 2023 | → |
| Serum Extracellular Vesicle-Derived hsa-miR-2277-3p and hsa-miR-6813-3p Are Potential Biomarkers for Major Depression: A Preliminary Study. | Seki I et al. | — | 2023 | → |
| Severe mental illness and the risk of breast cancer: A two-sample, two-step multivariable Mendelian randomization study. | Cui Y et al. | — | 2023 | → |
| Shared genetic architecture between irritable bowel syndrome and psychiatric disorders reveals molecular pathways of the gut-brain axis. | Tesfaye M et al. | — | 2023 | → |
| Shared genetic correlation and causal association between major depressive disorder and breast cancer. | Ohi K | — | 2023 | → |
| Shared Genetic Risk in the Association of Screen Time With Psychiatric Problems in Children. | Zhang Y et al. | — | 2023 | → |
| Single-Nucleus Transcriptional Profiling of GAD2-Positive Neurons From Mouse Lateral Habenula Reveals Distinct Expression of Neurotransmission- and Depression-Related Genes. | Green MV et al. | — | 2023 | → |
| Single-Nucleus Transcriptome Profiling of Dorsolateral Prefrontal Cortex: Mechanistic Roles for Neuronal Gene Expression, Including the 17q21.31 Locus, in PTSD Stress Response. | Chatzinakos C et al. | — | 2023 | → |
| Social isolation-induced transcriptomic changes in mouse hippocampus impact the synapse and show convergence with human genetic risk for neurodevelopmental phenotypes. | Laighneach A et al. | — | 2023 | → |
| Socioeconomic status and severe mental disorders: a bidirectional multivariable Mendelian randomisation study. | Andreu-Bernabeu Á et al. | — | 2023 | → |
| Specificity of polygenic signatures across symptom dimensions in bipolar disorder: an analysis of UK Bipolar Disorder Research Network data. | Allardyce J et al. | — | 2023 | → |
| Susceptibility and severity of COVID-19 and risk of psychiatric disorders in European populations: a Mendelian randomization study. | Xue H et al. | — | 2023 | → |
| The association between polygenic risk scores for mental disorders and social cognition: A scoping review. | Fusar-Poli L et al. | — | 2023 | → |
| The basolateral amygdala-anterior cingulate pathway contributes to depression-like behaviors and comorbidity with chronic pain behaviors in male mice. | Becker LJ et al. | — | 2023 | → |
| The brain-gut-microbiota interplay in depression: A key to design innovative therapeutic approaches. | Varesi A et al. | — | 2023 | → |
| The contributions of mitochondrial and nuclear mitochondrial genetic variation to neuroticism. | Xia C et al. | — | 2023 | → |
| The correlates of neonatal complement component 3 and 4 protein concentrations with a focus on psychiatric and autoimmune disorders. | Borbye-Lorenzen N et al. | — | 2023 | → |
| The genetic contribution to the comorbidity of depression and anxiety: a multi-site electronic health records study of almost 178 000 people. | Coombes BJ et al. | — | 2023 | → |
| The genetics of falling susceptibility and identification of causal risk factors. | Smith MC et al. | — | 2023 | → |
| The impact of COVID-19 on a college freshman sample reveals genetic and nongenetic forms of susceptibility and resilience to stress. | Turner CA et al. | — | 2023 | → |
| The impact of rare protein coding genetic variation on adult cognitive function. | Chen CY et al. | — | 2023 | → |
| The interactions between host genome and gut microbiome increase the risk of psychiatric disorders: Mendelian randomization and biological annotation. | Xiao L et al. | — | 2023 | → |
| The prediction of Alzheimer's disease through multi-trait genetic modeling. | Clark K et al. | — | 2023 | → |
| The relationship between COVID-19, depressive disorder, and anxiety: a bidirectional Mendelian randomization study. | Zihao L et al. | — | 2023 | → |
| The relationship between major depression and delirium: A two-sample Mendelian randomization analysis. | Li J et al. | — | 2023 | → |
| The role of depression and antidepressant treatment in antihypertensive medication adherence and persistence: Utilising electronic health record data. | Kariis HM et al. | — | 2023 | → |
| The Role of IgLON Cell Adhesion Molecules in Neurodegenerative Diseases. | Salluzzo M et al. | — | 2023 | → |
| The role of inflammatory biomarkers in the association between rheumatoid arthritis and depression: a Mendelian randomization study. | Xiang S et al. | — | 2023 | → |
| The role of NSAID in mediating the effect of genetically predicted major depressive disorder on osteomyelitis: A Mendelian randomization study. | Chen B et al. | — | 2023 | → |
| The UK BiLEVE and Mendelian randomisation: using multivariable instrumental variables to address "damned if you, damned if you don't" adjustment problems. | Woolf B et al. | — | 2023 | → |
| Towards a multilevel model of major depression: genes, immuno-metabolic function, and cortico-striatal signaling. | Paul ER et al. | — | 2023 | → |
| Transcriptional signatures of heroin intake and relapse throughout the brain reward circuitry in male mice. | Browne CJ et al. | — | 2023 | → |
| Transcriptome-Wide Structural Equation Modeling of 13 Major Psychiatric Disorders for Cross-Disorder Risk and Drug Repurposing. | Grotzinger AD et al. | — | 2023 | → |
| Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular-Structural-Functional Co-alterations. | Jiang L et al. | — | 2023 | → |
| Transcriptomics and magnetic resonance imaging in major psychiatric disorders. | Fan JW et al. | — | 2023 | → |
| Transition of allele-specific DNA hydroxymethylation at regulatory loci is associated with phenotypic variation in monozygotic twins discordant for psychiatric disorders. | Ye J et al. | — | 2023 | → |
| Understanding the causal relationships of attention-deficit/hyperactivity disorder with mental disorders and suicide attempt: a network Mendelian randomisation study. | Meisinger C et al. | — | 2023 | → |
| Understanding the relationship between loneliness, substance use traits and psychiatric disorders: A genetically informed approach. | Martin E et al. | — | 2023 | → |
| Unrevealing the shared genetic mechanisms underlying C-reactive protein and schizophrenia. | Yang Z et al. | — | 2023 | → |
| Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia. | Hsu YH et al. | — | 2023 | → |
| Variation along P2RX7 interacts with early traumas on severity of anxiety suggesting a role for neuroinflammation. | Kristof Z et al. | — | 2023 | → |
| Verbascoside: A neuroprotective phenylethanoid glycosides with anti-depressive properties. | Zhao Y et al. | — | 2023 | → |