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The antidepressant effects of ketamine are thought to depend on brain-derived neurotrophic factor (BDNF) genotype and dose. The purpose of this study was to characterize the dose-related antidepressant effects of ketamine in patients with treatment-resistant depression drawn from a Chinese population predominately possessing lower activity BDNF genotypes (Val/Met, Met/Met). We conducted a double-blind, randomized, parallel-group, placebo-controlled trial of a single ketamine infusion (saline, 0.2 mg/kg, 0.5 mg/kg). Patients (N=71; BDNF genotype: Val/Val (N=12, 17%), Val/Met (N=40, 56.3%), and Met/Met (N=19, 26.8%)) received mood ratings before infusion, after infusion, and for the subsequent 14 days. Plasma ketamine levels and BDNF genotypes were assessed. This study found a significant dose-related ketamine effect on scores on the Hamilton Depression Rating Scale (HAMD). The responder analysis (>50% reduction from baseline HAMD on at least 2 days between days 2 and 5) also revealed a significant dose-related effect (saline: 12.5%, 0.2 mg/kg: 39.1%; 0.5 mg/kg: 45.8%). This is the first report to our knowledge to demonstrate the dose-related efficacy of R/S-ketamine for treatment-resistant depression and the first to characterize ketamine effects in a genotyped Chinese population in which most (83%) patients possessed at least one copy of the lower functioning Met allele of the BDNF gene.

Background:A single subanesthetic infusion of the N-methyl-D-aspartate (NMDA) receptor antagonist ketamine has rapid and potent antidepressant properties in treatment-resistant major depressive disorder (TRD). As a family history of an alcohol use disorder is a positive predictor of ketamine’s antidepressant response and the strength of the association increases over time, we hypothesized that depressed subjects with a family history of an alcohol use disorder would have greater antidepressant durability and that riluzole would augment and/or extend ketamine’s antidepressant efficacy.Methods:Fifty-two TRD subjects received an open-label infusion of ketamine (0.5mg/kg over 40 minutes), and, four to six hours post-infusion, were randomized to either flexible-dose (100–200mg/day) riluzole or placebo in the following proportions: Family History Positive (FHP) riluzole (n = 10), FHP placebo (n = 9), Family History Negative (FHN) riluzole (n = 16), and FHN placebo (n = 17).Results:FHP subjects randomized to placebo had a greater antidepressant response than FHN subjects; however, contrary to our initial hypothesis, there was no significant difference in antidepressant efficacy with riluzole. Although potentially underpowered, there was no difference in overall time-to-relapse based on randomization status (riluzole responders: n = 15, placebo responders: n = 17). Yet, time-to-relapse was longer in FHP placebo responders (n = 8) compared to FHN placebo responders (n = 9) with, again, no significant difference in time-to-relapse in FHP riluzole responders (n = 6) compared to FHN riluzole responders (n = 9).Conclusions:Ketamine’s extended antidepressant durability in FHP TRD should be considered in the design and analysis of ketamine depression trials.

To improve the 'personalized-medicine' approach to the treatment of depression, we need to identify biomarkers that, assessed before starting treatment, predict future response to antidepressants ('predictors'), as well as biomarkers that are targeted by antidepressants and change longitudinally during the treatment ('targets'). In this study, we tested the leukocyte mRNA expression levels of genes belonging to glucocorticoid receptor (GR) function (FKBP-4, FKBP-5, and GR), inflammation (interleukin (IL)-1α, IL-1β, IL-4, IL-6, IL-7, IL-8, IL-10, macrophage inhibiting factor (MIF), and tumor necrosis factor (TNF)-α), and neuroplasticity (brain-derived neurotrophic factor (BDNF), p11 and VGF), in healthy controls (n=34) and depressed patients (n=74), before and after 8 weeks of treatment with escitalopram or nortriptyline, as part of the Genome-based Therapeutic Drugs for Depression study. Non-responders had higher baseline mRNA levels of IL-1β (+33%), MIF (+48%), and TNF-α (+39%). Antidepressants reduced the levels of IL-1β (-6%) and MIF (-24%), and increased the levels of GR (+5%) and p11 (+8%), but these changes were not associated with treatment response. In contrast, successful antidepressant response was associated with a reduction in the levels of IL-6 (-9%) and of FKBP5 (-11%), and with an increase in the levels of BDNF (+48%) and VGF (+20%)-that is, response was associated with changes in genes that did not predict, at the baseline, the response. Our findings indicate a dissociation between 'predictors' and 'targets' of antidepressant responders. Indeed, while higher levels of proinflammatory cytokines predict lack of future response to antidepressants, changes in inflammation associated with antidepressant response are not reflected by all cytokines at the same time. In contrast, modulation of the GR complex and of neuroplasticity is needed to observe a therapeutic antidepressant effect.

Genomic analysis of 5,303 Chinese women with recurrent major depressive disorder (MDD) enables the identification and replication of two genome-wide significant loci contributing to risk of MDD on chromosome 10: one near the SIRT1 gene; the other in an intron of the LHPP gene. Genetic risk factors for depression This genomic analysis of more than 5,000 Chinese women with recurrent major depressive disorder (MDD) has identified and replicated two genome-wide significant loci contributing to risk of MDD on chromosome 10. One is near the sirtuin1 ( SIRT1 ) gene, and the other is in an intron of the phospholysine phosphohistidine inorganic pyrophosphate phosphatase ( LHPP ) gene. The authors suggest that the association close to SIRT1 may implicate abnormalities in mitochondria as risk factors for the disease. Major depressive disorder (MDD), one of the most frequently encountered forms of mental illness and a leading cause of disability worldwide 1 , poses a major challenge to genetic analysis. To date, no robustly replicated genetic loci have been identified 2 , despite analysis of more than 9,000 cases 3 . Here, using low-coverage whole-genome sequencing of 5,303 Chinese women with recurrent MDD selected to reduce phenotypic heterogeneity, and 5,337 controls screened to exclude MDD, we identified, and subsequently replicated in an independent sample, two loci contributing to risk of MDD on chromosome 10: one near the SIRT1 gene ( P  = 2.53 × 10 −10 ), the other in an intron of the LHPP gene ( P = 6.45 × 10 −12 ). Analysis of 4,509 cases with a severe subtype of MDD, melancholia, yielded an increased genetic signal at the SIRT1 locus. We attribute our success to the recruitment of relatively homogeneous cases with severe illness.

Major mood disorders, which primarily include bipolar disorder and major depressive disorder, are the leading cause of disability worldwide and pose a major challenge in identifying robust risk genes. Here, we present data from independent large-scale clinical data sets (including 29 557 cases and 32 056 controls) revealing brain expressed protocadherin 17 (PCDH17) as a susceptibility gene for major mood disorders. Single-nucleotide polymorphisms (SNPs) spanning the PCDH17 region are significantly associated with major mood disorders; subjects carrying the risk allele showed impaired cognitive abilities, increased vulnerable personality features, decreased amygdala volume and altered amygdala function as compared with non-carriers. The risk allele predicted higher transcriptional levels of PCDH17 mRNA in postmortem brain samples, which is consistent with increased gene expression in patients with bipolar disorder compared with healthy subjects. Further, overexpression of PCDH17 in primary cortical neurons revealed significantly decreased spine density and abnormal dendritic morphology compared with control groups, which again is consistent with the clinical observations of reduced numbers of dendritic spines in the brains of patients with major mood disorders. Given that synaptic spines are dynamic structures which regulate neuronal plasticity and have crucial roles in myriad brain functions, this study reveals a potential underlying biological mechanism of a novel risk gene for major mood disorders involved in synaptic function and related intermediate phenotypes.

Psychiatric disorders are the leading cause of disability worldwide while the pathogenesis remains unclear. Genome-wide association studies (GWASs) have made great achievements in detecting disease-related genetic variants. However, functional information on the underlying biological processes is often lacking. Current reports propose the use of metabolic traits as functional intermediate phenotypes (the so-called genetically determined metabotypes or GDMs) to reveal the biological mechanisms of genetics in human diseases. Here we conducted a two-sample Mendelian randomization analysis that uses GDMs to assess the causal effects of 486 human serum metabolites on 5 major psychiatric disorders, which respectively were schizophrenia (SCZ), major depression (MDD), bipolar disorder (BIP), autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD). Using genetic variants as proxies, our study has identified 137 metabolites linked to the risk of psychiatric disorders, including 2-methoxyacetaminophen sulfate, which affects SCZ (P = 1.7 × 10–5) and 1-docosahexaenoylglycerophosphocholine, which affects ADHD (P = 5.6 × 10–5). Fourteen significant metabolic pathways involved in the 5 psychiatric disorders assessed were also detected, such as glycine, serine, and threonine metabolism for SCZ (P = .0238), Aminoacyl-tRNA biosynthesis for both MDD (P = .0144) and ADHD (P = .0029). Our study provided novel insights into integrating metabolomics with genomics in order to understand the mechanisms underlying the pathogenesis of human diseases.

Genetic predisposition may contribute to the differences in drug-specific, class-specific or antidepressant-wide treatment resistance. Clinical studies with the genetic data are often limited in sample sizes. Drug response obtained from self-reports may offer an alternative approach to conduct a study with much larger sample size. Using the phenotype data collected from 23andMe ‘Antidepressant Efficacy and Side Effects’ survey and genotype data from 23andMe’s research participants, we conducted genome-wide association study (GWAS) on subjects of European ancestry using four groups of phenotypes (a) non-treatment-resistant depression ( n =7795) vs treatment-resistant depression (TRD, n =1311), (b) selective serotonin reuptake inhibitors (SSRI) responders ( n =6348) vs non-responders ( n =3340), (c) citalopram/escitalopram responders ( n =2963) vs non-responders ( n =2005), and (d) norepinephrine–dopamine reuptake inhibitor (NDRI, bupropion) responders ( n =2675) vs non-responders ( n =1861). Each of these subgroups was also compared with controls ( n ~ 190 000). The most significant association was from bupropion responders vs non-responders analysis. Variant rs1908557 ( P =2.6 × 10 −8 , OR=1.35) passed the conventional genome-wide significance threshold ( P =5 × 10 −8 ) and was located within the intron of human spliced expressed sequence tags in chromosome 4. Gene sets associated with long-term depression, circadian rhythm and vascular endothelial growth factor (VEGF) pathway were enriched in the bupropion analysis. No single-nucleotide polymorphism passed genome-wide significance threshold in other analyses. The heritability estimates for each response group compared with controls were between 0.15 and 0.25, consistent with the known heritability for major depressive disorder.

Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC. Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals). Positive genetic correlation was observed between MD and AD (rgMD-AD = + 0.47, P = 6.6 × 10-10). AC-quantity showed positive genetic correlation with both AD (rgAD-AC quantity = + 0.75, P = 1.8 × 10-14) and MD (rgMD-AC quantity = + 0.14, P = 2.9 × 10-7), while there was negative correlation of AC-frequency with MD (rgMD-AC frequency = -0.17, P = 1.5 × 10-10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10-6). There was no evidence for reverse causation. This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.

Electroconvulsive therapy (ECT) is an effective antidepressant treatment. The mechanisms behind the therapeutic effect are not fully understood, and reliable biomarkers for response are needed. Epigenetic modifications, such as DNA methylation (DNAm), can reflect both genetic and environmental impacts; they may shed light on the mechanisms behind treatment effects and they have the potential to inform response prediction. We performed an epigenome-wide association study (EWAS) in peripheral blood from patients before and after ECT in a Norwegian cohort (n = 65). The methylation levels of 12 differentially methylated CpG positions (DMPs) and 18 differentially methylated regions (DMRs) were significantly associated with percent clinical response. In addition, 29 DMPs and 23 DMRs were significantly associated with remission (Montgomery and Åsberg Depression Rating Scale MADRS < 10 post treatment). Two DMRs were also significantly associated with percent response at baseline and four DMRs were significantly associated with remission at baseline (FDR < 0.05). We did not identify any longitudinal (pre-post) changes in DNAm. We further performed the first meta-analysis (n = 99) between ECT cohorts, combining this Norwegian cohort and a German ECT cohort (n = 34). Seven of the DMRs found to be associated with response in the meta-analyses were previously identified in the Norwegian or the German cohort (FDR < 0.05). Methylation risk scores (MS) calculated using DMPs associated with ECT in the Norwegian cohort showed promising association with response to ECT in the German cohort (p = 0.06). Finally, we found increased neutrophil to lymphocyte ratios, calculated from estimated cell proportions, to be associated with remission (p < 0.003) in the Norwegian cohort.

Response and remission defined by cut-off values on the last observed depression severity score are commonly used as outcome criteria in clinical trials, but ignore the time course of symptomatic change and may lead to inefficient analyses. We explore alternative categorization of outcome by naturally occurring trajectories of symptom change. Growth mixture models were applied to repeated measurements of depression severity in 807 participants with major depression treated for 12 weeks with escitalopram or nortriptyline in the part-randomized Genome-based Therapeutic Drugs for Depression study. Latent trajectory classes were validated as outcomes in drug efficacy comparison and pharmacogenetic analyses. The final two-piece growth mixture model categorized participants into a majority (75%) following a gradual improvement trajectory and the remainder following a trajectory with rapid initial improvement. The rapid improvement trajectory was over-represented among nortriptyline-treated participants and showed an antidepressant-specific pattern of pharmacogenetic associations. In contrast, conventional response and remission favoured escitalopram and produced chance results in pharmacogenetic analyses. Controlling for drop-out reduced drug differences on response and remission but did not affect latent trajectory results. Latent trajectory mixture models capture heterogeneity in the development of clinical response after the initiation of antidepressants and provide an outcome that is distinct from traditional endpoint measures. It differentiates between antidepressants with different modes of action and is robust against bias due to differential discontinuation.