Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17–29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn’s disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

The stress hormone-regulating hypothalamic-pituitary-adrenal (HPA) axis has been implicated in the causality as well as the treatment of depression. To investigate a possible association between genes regulating the HPA axis and response to antidepressants and susceptibility for depression, we genotyped single-nucleotide polymorphisms in eight of these genes in depressed individuals and matched controls. We found significant associations of response to antidepressants and the recurrence of depressive episodes with single-nucleotide polymorphisms in FKBP5, a glucocorticoid receptor-regulating cochaperone of hsp-90, in two independent samples. These single-nucleotide polymorphisms were also associated with increased intracellular FKBP5 protein expression, which triggers adaptive changes in glucocorticoid receptor and, thereby, HPA-axis regulation. Individuals carrying the associated genotypes had less HPA-axis hyperactivity during the depressive episode. We propose that the FKBP5 variant-dependent alterations in HPA-axis regulation could be related to the faster response to antidepressant drug treatment and the increased recurrence of depressive episodes observed in this subgroup of depressed individuals. These findings support a central role of genes regulating the HPA axis in the causality of depression and the mechanism of action of antidepressant drugs.

Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P< 0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5×10−8), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083–53 822 102, minimum P= 5.9×10−9 at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.

Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

The clinical efficacy of a systemically administered drug acting on the central nervous system depends on its ability to pass the blood-brain barrier, which is regulated by transporter molecules such as ABCB1 (MDR1). Here we report that polymorphisms in the ABCB1 gene predict the response to antidepressant treatment in those depressed patients receiving drugs that have been identified as substrates of ABCB1 using abcb1ab double-knockout mice. Our results indicate that the combined consideration of both the medication's capacity to act as an ABCB1-transporter substrate and the patient's ABCB1 genotype are strong predictors for achieving a remission. This finding can be viewed as a further step into personalized antidepressant treatment.