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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.

Treatment-resistant depression (TRD) is a major contributor to the disability caused by major depressive disorder (MDD). Primary care electronic health records provide an easily accessible approach to investigate TRD clinical and genetic characteristics. MDD defined from primary care records in UK Biobank (UKB) and EXCEED studies was compared with other measures of depression and tested for association with MDD polygenic risk score (PRS). Using prescribing records, TRD was defined from at least two switches between antidepressant drugs, each prescribed for at least 6 weeks. Clinical-demographic characteristics, SNP-based heritability (h2SNP) and genetic overlap with psychiatric and non-psychiatric traits were compared in TRD and non-TRD MDD cases. In 230,096 and 8926 UKB and EXCEED participants with primary care data, respectively, the prevalence of MDD was 8.7% and 14.2%, of which 13.2% and 13.5% was TRD, respectively. In both cohorts, MDD defined from primary care records was strongly associated with MDD PRS, and in UKB it showed overlap of 71–88% with other MDD definitions. In UKB, TRD vs healthy controls and non-TRD vs healthy controls h2SNP was comparable (0.25 [SE = 0.04] and 0.19 [SE = 0.02], respectively). TRD vs non-TRD was positively associated with the PRS of attention deficit hyperactivity disorder, with lower socio-economic status, obesity, higher neuroticism and other unfavourable clinical characteristics. This study demonstrated that MDD and TRD can be reliably defined using primary care records and provides the first large scale population assessment of the genetic, clinical and demographic characteristics of TRD.

Treatment-resistant depression (TRD), defined as the failure to achieve adequate response to at least two antidepressant trials, affects 20–30% of patients with major depressive disorder and poses substantial personal and socioeconomic burdens. This review aimed to synthesize current knowledge on the genetic, epigenetic, and neurobiological underpinnings of TRD to understand its pathophysiology better and inform future treatment strategies. A systematic search identified relevant studies focusing on genetic predispositions, epigenetic modifications, structural and functional brain alterations, the role of chronic inflammation, and deficits in neuroplasticity and neurogenesis associated with TRD. Findings highlight the involvement of polymorphisms in genes regulating neurotransmission, neuroplasticity, and stress response, though replication across studies remains inconsistent. Genome-wide association studies suggest polygenic contributions but are limited by small sample sizes and heterogeneous definitions of TRD. Emerging evidence points to aberrant DNA methylation, histone modifications, and dysregulated non-coding RNAs as potential mediators of treatment resistance. Neuroimaging studies reveal TRD-specific patterns, particularly altered default mode network connectivity and white matter disruptions, supporting its distinction as a subtype of depression. Collectively, the evidence underscores TRD as a multifactorial condition shaped by genetic and neurobiological factors, while emphasizing the need for standardized definitions, larger cohorts, and longitudinal designs to advance the field.

Whether microRNAs (miRNAs) from plasma exosomes might be dysregulated in patients with depression, especially treatment-resistant depression (TRD), remains unclear, based on study of which novel biomarkers and therapeutic targets could be discovered. To this end, a small sample study was performed by isolation of plasma exosomes from patients with TRD diagnosed by Hamilton scale. In this study, 4 peripheral plasma samples from patients with TRD and 4 healthy controls were collected for extraction of plasma exosomes. Exosomal miRNAs were analyzed by miRNA sequencing, followed by image collection, expression difference analysis, target gene GO enrichment analysis, and KEGG pathway enrichment analysis. Compared with the healthy controls, 2 miRNAs in the plasma exosomes of patients with TRD showed significant differences in expression, among which has-miR-335-5p were significantly upregulated and has-miR-1292-3p were significantly downregulated. Go and KEGG analysis showed that dysregulated miRNAs affect postsynaptic density and axonogenesis as well as the signaling pathway of axon formation and cell growths. The identification of these miRNAs and their target genes may provide novel biomarkers for improving diagnosis accuracy and treatment effectiveness of TRD.

Late-life depression (LLD) is often accompanied by medical comorbidities such as psychiatric disorders and cardiovascular diseases, posing challenges to antidepressant treatment. Recent studies highlighted significant associations between treatment-resistant depression (TRD) and polygenic risk score (PRS) for attention deficit hyperactivity disorder (ADHD) in adults as well as a negative association between antidepressant symptom improvement with both schizophrenia and bipolar. Here, we sought to validate these findings with symptom remission in LLD. We analyzed the Incomplete Response in Late Life Depression: Getting to Remission (IRL-GRey) sample consisting of adults aged 60+ with major depression ( N  = 342) treated with venlafaxine for 12 weeks. We constructed PRSs for ADHD, depression, schizophrenia, bipolar disorder, neuroticism, general intelligence, antidepressant symptom remission and antidepressant percentage symptom improvement using summary statistics from the Psychiatric Genomics Consortium and the GWAS Catalog. Logistic regression was used to test the association of PRSs with venlafaxine symptom remission and percentage symptom improvement, co-varying for the genomic principal components, age, sex and depressive symptoms severity at baseline. We found a nominal (i.e., p value ≤ 0.05) association between symptom remission and both PRS for ADHD and (OR = 1.36 [1.07, 1.73], p  = 0.011) and PRS for bipolar disorder (OR = 0.75 [0.58, 0.97], p  = 0.031), as well as between percentage symptom improvement and PRS for general intelligence (beta = 6.81 (SE = 3.122), p  = 0.03). However, the ADHD association was in the opposite direction as expected, and both associations did not survive multiple testing corrections. Altogether, these findings suggest that previous findings regarding ADHD PRS and antidepressant response (measured with various outcomes) do not replicate in older adults.

Background Transcranial magnetic stimulation (TMS) is an established treatment for major depressive disorder (MDD), yet response rates remain suboptimal and biomarkers predictive of treatment outcomes are currently lacking. Recently, DNA methylation (DNAm) has shown promise as an epigenetic predictor of antidepressant and electroconvulsive therapy treatment outcomes but no study to our knowledge has characterized DNAm profiles of treatment outcomes in the context of TMS. Here, we present the first genome-scale DNAm analysis of TMS outcomes in patients with treatment-resistant depression (TRD). Methods Peripheral blood samples from 60 TRD patients were collected prior to a standard 36-session TMS course. DNAm was profiled using the Illumina EPIC array and filtered to retain only the top 5% most variable probes for subsequent analysis in relation to three treatment outcomes in an analytic sample of 46 patients: treatment response (> 50% PHQ-9 reduction), symptom trajectory (ΔPHQ-9), and remission (PHQ-9 < 5). Results Methylated CpG Set Enrichment Analysis ( mCSEA ) identified 67, 23, and 163 differentially methylated regions (DMRs) associated with treatment response, symptom trajectory, and remission, respectively (FDR < 0.05). Sixteen DMRs were common across all outcomes, implicating genes involved in neurodevelopment ( HOXA4 , HOXA5 ), immune signaling ( RUNX1 , OTUD5 ), and synaptic function ( EFNB1 , RAP2C). Targeted analysis of 84 CpGs in the BDNF promoter revealed 10 nominally significant CpGs that differentiated responders from non-responders. Several DMRs showed strong blood–brain methylation concordance ( r  > 0.5), supporting their potential relevance to central nervous system mechanisms. Conclusions Despite the limited sample size, these findings suggest distinct epigenetic signatures prior to treatment that are associated with TMS outcomes, supporting the potential utility of DNAm as a biomarker for response stratification in TRD.

Electroconvulsive therapy (ECT) is an effective and rapid neuromodulatory intervention for treatment-resistant major depressive disorders (MDD). However, the precise mechanisms underlying their efficacies remain unclear. Resting-state functional magnetic resonance imaging (fMRI) data were collected from 84 individuals with MDD and healthy controls before and after ECT, and coefficient of variation of the BOLD signal (CVBOLD) analysis was combined with region of interest (ROI) functional connectivity (FC) analysis. To assess the reliability of the antidepressant mechanism of ECT, we analyzed the changes in CVBOLD in a separate cohort consisting of 35 patients with MDD who underwent ECT. Moreover, transcriptomic and neurotransmitter receptor data were used to reveal the genetic and molecular bases of the changes in CVBOLD. Patients with MDD who underwent ECT demonstrated increased CVBOLD in the left angular cortex and left precuneus. Following ECT, an increase in FC between the left precuneus and right lingual lobes was associated with improvements in Hamilton Depression Rating Scale (HAMD) scores. validation analysis consistently demonstrated similar changes in CVBOLD in two independent cohorts of patients with MDD. Moreover, these changes in CVBOLD were closely associated with thyroid hormone synthesis, oxidative phosphorylation, endocytosis, and the insulin signaling pathway, and were significantly correlated with the receptor/transporter density of serotonin and dopamine. These findings suggest that ECT modulates abnormal functions in the left angular cortex and left precuneus, leading to widespread changes in functional connectivity and neuroplasticity, especially in the default mode network, and exerts an antidepressant effect.

The “antidepressant efficacy” survey (AES) was deployed to > 50,000 23andMe, Inc. research participants to investigate the genetic basis of treatment-resistant depression (TRD) and non-treatment-resistant depression (NTRD). Genome-wide association studies (GWAS) were performed, including TRD vs. NTRD, selective serotonin reuptake inhibitor (SSRI) responders vs. non-responders, serotonin-norepinephrine reuptake inhibitor (SNRI) responders vs. non-responders, and norepinephrine-dopamine reuptake inhibitor responders vs. non-responders. Only the SSRI association reached the genome-wide significance threshold ( p  < 5 × 10 −8 ): one genomic region in RNF219-AS1 (SNP rs4884091, p  = 2.42 × 10 −8 , OR = 1.21); this association was also observed in the meta-analysis (13,130 responders vs. 6,610 non-responders) of AES and an earlier “antidepressant efficacy and side effects” survey (AESES) cohort. Meta-analysis for SNRI response phenotype derived from AES and AESES (4030 responders vs. 3049 non-responders) identified another genomic region (lead SNP rs4955665, p  = 1.62 × 10 −9 , OR = 1.25) in an intronic region of MECOM passing the genome-wide significance threshold. Meta-analysis for the TRD phenotype (31,068 NTRD vs 5,714 TRD) identified one additional genomic region (lead SNP rs150245813, p  = 8.07 × 10 −9 , OR = 0.80) in 10p11.1 passing the genome-wide significance threshold. A stronger association for rs150245813 was observed in current study ( p  = 7.35 × 10 −7 , OR = 0.79) than the previous study ( p  = 1.40 × 10 −3 , OR = 0.81), and for rs4955665, a stronger association in previous study ( p  = 1.21 × 10 −6 , OR = 1.27) than the current study ( p  = 2.64 × 10 −4 , OR = 1.21). In total, three novel loci associated with SSRI or SNRI (responders vs. non-responders), and NTRD vs TRD were identified; gene level association and gene set enrichment analyses implicate enrichment of genes involved in immune process.

Treatment-resistant depression (TRD) is the most problematic outcome of depression in terms of functional impairment, suicidal thoughts and decline in physical health.AimsTo investigate the genetic predictors of TRD using a genome-wide approach to contribute to the development of precision medicine. A sample recruited by the European Group for the Study of Resistant Depression (GSRD) including 1148 patients with major depressive disorder (MDD) was characterised for the occurrence of TRD (lack of response to at least two adequate antidepressant treatments) and genotyped using the Infinium PsychArray. Three clinically relevant patient groups were considered: TRD, responders and non-responders to the first antidepressant trial, thus outcomes were based on comparisons of these groups. Genetic analyses were performed at the variant, gene and gene-set (i.e. functionally related genes) level. Additive regression models of the outcomes and relevant covariates were used in the GSRD participants and in a fixed-effect meta-analysis performed between GSRD, STAR*D (n = 1316) and GENDEP (n = 761) participants. No individual polymorphism or gene was associated with TRD, although some suggestive signals showed enrichment in cytoskeleton regulation, transcription modulation and calcium signalling. Two gene sets (GO:0043949 and GO:0000183) were associated with TRD versus response and TRD versus response and non-response to the first treatment in the GSRD participants and in the meta-analysis, respectively (corrected P = 0.030 and P = 0.027). The identified gene sets are involved in cyclic adenosine monophosphate mediated signal and chromatin silencing, two processes previously implicated in antidepressant action. They represent possible biomarkers to implement personalised antidepressant treatments and targets for new antidepressants.Declaration of interestD.S. has received grant/research support from GlaxoSmithKline and Lundbeck; has served as a consultant or on advisory boards for AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Janssen and Lundbeck. S.M. has been a consultant or served on advisory boards for: AstraZeneca, Bristol-Myers Squibb, Forest, Johnson & Johnson, Leo, Lundbeck, Medelink, Neurim, Pierre Fabre, Richter. S.K. has received grant/research support from Eli Lilly, Lundbeck, Bristol-Myers Squibb, GlaxoSmithKline, Organon, Sepracor and Servier; has served as a consultant or on advisory boards for AstraZeneca, Bristol-Myers Squibb, GlaxoSmithKline, Eli Lilly, Lundbeck, Pfizer, Organon, Schwabe, Sepracor, Servier, Janssen and Novartis; and has served on speakers' bureaus for AstraZeneca, Eli Lily, Lundbeck, Schwabe, Sepracor, Servier, Pierre Fabre, Janssen and Neuraxpharm. J.Z. has received grant/research support from Lundbeck, Servier, Brainsway and Pfizer, has served as a consultant or on advisory boards for Servier, Pfizer, Abbott, Lilly, Actelion, AstraZeneca and Roche and has served on speakers' bureaus for Lundbeck, Roch, Lilly, Servier, Pfizer and Abbott. J.M. is a member of the Board of the Lundbeck International Neuroscience Foundation and of Advisory Board of Servier. A.S. is or has been consultant/speaker for: Abbott, AbbVie, Angelini, Astra Zeneca, Clinical Data, Boehringer, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline, Innovapharma, Italfarmaco, Janssen, Lundbeck, Naurex, Pfizer, Polifarma, Sanofi and Servier. C.M.L. receives research support from RGA UK Services Limited.

Treatment-resistant depression (TRD) occurs in ~30% of patients with major depressive disorder (MDD) but the genetics of TRD was previously poorly investigated. Whole exome sequencing and genome-wide genotyping were available in 1209 MDD patients after quality control. Antidepressant response was compared to non-response to one treatment and non-response to two or more treatments (TRD). Differences in the risk of carrying damaging variants were tested. A score expressing the burden of variants in genes and pathways was calculated weighting each variant for its functional (Eigen) score and frequency. Gene-based and pathway-based scores were used to develop predictive models of TRD and non-response using gradient boosting in 70% of the sample (training) which were tested in the remaining 30% (testing), evaluating also the addition of clinical predictors. Independent replication was tested in STAR*D and GENDEP using exome array-based data. TRD and non-responders did not show higher risk to carry damaging variants compared to responders. Genes/pathways associated with TRD included those modulating cell survival and proliferation, neurodegeneration, and immune response. Genetic models showed significant prediction of TRD vs. response and they were improved by the addition of clinical predictors, but they were not significantly better than clinical predictors alone. Replication results were driven by clinical factors, except for a model developed in subjects treated with serotonergic antidepressants, which showed a clear improvement in prediction at the extremes of the genetic score distribution in STAR*D. These results suggested relevant biological mechanisms implicated in TRD and a new methodological approach to the prediction of TRD.