Chemokines are increasingly recognised as playing a role in depression. Here we meta-analyse the data on concentrations of all chemokines in patients diagnosed with a major depression versus healthy controls. We included studies which utilised Diagnostic and Statistical Manual (DSM)-IV diagnostic criteria for major depression, participants free from major medical conditions, studies with healthy controls, and unstimulated measurements of chemokines. We only included chemokines which had ≥3 studies performed. Two chemokines and 15 studies in total met criteria for this meta-analysis; 8 for Monocyte Chemotactic Protein (MCP)-1/CCL2 (n=747), and 7 for Interleukin (IL)-8/CXCL8 (n=560). There were significantly higher concentrations of CCL2/MCP-1 in depressed subjects compared with control subjects - overall mean difference of 36.43pg/mL (95% CI: 2.43 to 70.42). There was significant heterogeneity across these studies (I2=98.5%). The estimates of mean difference between the control and depression groups did not remain significant when the trim-and-fill procedure was used to correct for publication bias. There was no significant difference in concentrations of IL-8/CXCL8 in depressed subjects compared with control subjects. Significant heterogeneity was found across these studies (I2=96.7%). The estimates of mean difference between the control and depression groups remained non-significant when the trim-and-fill procedure was used to correct for publication bias. This meta-analysis reports significantly heterogeneity in this field among studies. There are higher concentrations of the chemokine MCP-1/CCL2 in depressed subjects compared with control subjects, and no differences for IL-8/CXCL8. More high quality research and consistent methodologies are needed in this important area of enquiry.

Objective

More than 90% of people who attempt suicide have a psychiatric diagnosis; however, twin and family studies suggest that the genetic etiology of suicide attempt is partially distinct from that of the psychiatric disorders themselves. The authors present the largest genome-wide association study (GWAS) on suicide attempt, using cohorts of individuals with major depressive disorder, bipolar disorder, and schizophrenia from the Psychiatric Genomics Consortium.

Methods

The samples comprised 1,622 suicide attempters and 8,786 nonattempters with major depressive disorder; 3,264 attempters and 5,500 nonattempters with bipolar disorder; and 1,683 attempters and 2,946 nonattempters with schizophrenia. A GWAS on suicide attempt was performed by comparing attempters to nonattempters with each disorder, followed by a meta-analysis across disorders. Polygenic risk scoring was used to investigate the genetic relationship between suicide attempt and the psychiatric disorders.

Results

Three genome-wide significant loci for suicide attempt were found: one associated with suicide attempt in major depressive disorder, one associated with suicide attempt in bipolar disorder, and one in the meta-analysis of suicide attempt in mood disorders. These associations were not replicated in independent mood disorder cohorts from the UK Biobank and iPSYCH. No significant associations were found in the meta-analysis of all three disorders. Polygenic risk scores for major depression were significantly associated with suicide attempt in major depressive disorder (R²=0.25%), bipolar disorder (R²=0.24%), and schizophrenia (R²=0.40%).

Conclusions

This study provides new information on genetic associations and demonstrates that genetic liability for major depression increases risk for suicide attempt across psychiatric disorders. Further collaborative efforts to increase sample size may help to robustly identify genetic associations and provide biological insights into the etiology of suicide attempt.

Background

Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.

Methods

We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.

Results

Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10^-8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10^-6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10^-7; rs73033497, p = 8.8 × 10^-7; rs7914279, p = 6.4 × 10^-7), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10^-7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10^-7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10^-7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05).

Conclusions

In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.

Background

Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders.

Methods

We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.

Results

Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged.

Conclusions

Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.