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Ketamine commonly and rapidly induces dissociative and other altered states of consciousness (ASCs) in humans. However, the neural mechanisms that contribute to these experiences remain unknown. We used functional neuroimaging to engage key regions of the brain’s affective circuits during acute ketamine-induced ASCs within a randomized, multi-modal, placebo-controlled design examining placebo, 0.05 mg/kg ketamine, and 0.5 mg/kg ketamine in nonclinical adult participants (NCT03475277). Licensed clinicians monitored infusions for safety. Linear mixed effects models, analysis of variance, t-tests, and mediation models were used for statistical analyses. Our design enabled us to test our pre-specified primary and secondary endpoints, which were met: effects of ketamine across dose conditions on (1) emotional task-evoked brain activity, and (2) sub-components of dissociation and other ASCs. With this design, we also could disentangle which ketamine-induced affective brain states are dependent upon specific aspects of ASCs. Differently valenced ketamine-induced ASCs mediated opposing effects on right anterior insula activity. Participants experiencing relatively higher depersonalization induced by 0.5 mg/kg of ketamine showed relief from negative brain states (reduced task-evoked right anterior insula activity, 0.39 SD). In contrast, participants experiencing dissociative amnesia showed an exacerbation of insula activity (0.32 SD). These results in nonclinical participants may shed light on the mechanisms by which specific dissociative states predict response to ketamine in depressed individuals. The neural mechanisms underlying ketamine-induced altered states of consciousness are not well understood. Here, the authors show that depersonalization and dissociative amnesia related to ketamine have opposing effects on the activity of the right anterior insula in response to social threat.

Background Although repetitive transcranial magnetic stimulation (‘TMS’) is becoming a gold standard treatment for pharmacoresistant depression, we lack neural target biomarkers for identifying who is most likely to respond to TMS and why. To address this gap in knowledge we evaluate neural targets defined by activation and functional connectivity of the dorsolateral prefrontal cortex-anchored cognitive control circuit, regions of the default mode network and attention circuit, and interactions with the subgenual anterior cingulate. We evaluate whether these targets and interactions between them change in a dose-dependent manner, whether changes in these neural targets correspond to changes in cognitive behavioral performance, and whether baseline and early change in neural target and cognitive behavioral performance predict subsequent symptom severity, suicidality, and quality of life outcomes. This study is designed as a pragmatic, mechanistic trial partnering with the National Clinical TMS Program of the Veteran’s Health Administration. Methods Target enrollment consists of 100 veterans with pharmacoresistant Major Depressive Disorder (MDD). All veterans will receive a clinical course of TMS and will be assessed at ‘baseline’ pre-TMS commencement, ‘first week’ after initiation of TMS (targeting five sessions) and ‘post-treatment’ at the completion of TMS (targeting 30 sessions). Veterans will be assessed using functional magnetic resonance imaging (fMRI), a cognitive behavioral performance battery, and established questionnaires. Multivariate linear mixed models will be used to assess whether neural targets change with TMS as a function of dose (Aim 1), whether extent and change of neural target relates to and predicts extent of behavioral performance (Aim 3), and whether extent of neural target change predicts improvement in symptom severity, suicidality, and quality of life (Aim 3). For all three aims, we will also assess the contribution of baseline moderators such as biological sex and age. Discussion To our knowledge, our study will be the first pragmatic, mechanistic observational trial to use fMRI imaging and cognitive-behavioral performance as biomarkers of TMS treatment response in pharmacoresistant MDD. The results of this trial will allow providers to select suitable candidates for TMS treatment and better predict treatment response by assessing circuit connectivity and cognitive-behavioral performance at baseline and during early treatment. Trial registration ClinicalTrials.gov NCT04663481 , December 5th, 2020, retrospectively registered. The first veteran was enrolled October 30th, 2020.

Psychiatry is dedicated to understanding mental disorders and helping people struggling with them live fulfilling lives. Although current treatment modalities can be remarkably effective at improving patients' quality of life and mitigating the burden of symptoms for disorders like depression, bipolar disorder, or posttraumatic stress disorder, finding the right treatment for an individual can be a long and fraught process during which symptoms can worsen the risks associated with other health conditions. Precision psychiatry, as outlined in this groundbreaking book, presents a new path forward. By integrating findings from basic and clinical neuroscience, clinical practice, and population-level data, the field seeks to develop therapeutic approaches tailored for specific individuals with a specific constellation of health issues, characteristics, strengths, and symptoms. This guide harnesses the expertise of more than three dozen contributors in diverse areas of interest, including neuroimaging, electrophysiology, neurocognition, behavioral science, machine learning, and pharmacotherapy, to examine the current state of precision medicine in psychiatry and explore future areas of advancement. Numerous case examples illustrate and apply the principles of precision psychiatry to mood and anxiety disorders, as well as schizophrenia, in adult patients, emphasizing the push to develop biomarkers and algorithms that will identify subtypes of patients that may be underserved by conventional therapies. In these pages, educators, trainees, and clinicians will find the latest research in precise classification, treatment planning, and early identification across a spectrum of psychiatric disorders—and the foundation for a future where one-size-fits-all treatments are replaced by modalities optimized for individual patients across all stages of a disorder.

There is an urgent need to derive quantitative measures based on coherent neurobiological dysfunctions or ‘biotypes’ to enable stratification of patients with depression and anxiety. We used task-free and task-evoked data from a standardized functional magnetic resonance imaging protocol conducted across multiple studies in patients with depression and anxiety when treatment free ( n  = 801) and after randomization to pharmacotherapy or behavioral therapy ( n  = 250). From these patients, we derived personalized and interpretable scores of brain circuit dysfunction grounded in a theoretical taxonomy. Participants were subdivided into six biotypes defined by distinct profiles of intrinsic task-free functional connectivity within the default mode, salience and frontoparietal attention circuits, and of activation and connectivity within frontal and subcortical regions elicited by emotional and cognitive tasks. The six biotypes showed consistency with our theoretical taxonomy and were distinguished by symptoms, behavioral performance on general and emotional cognitive computerized tests, and response to pharmacotherapy as well as behavioral therapy. Our results provide a new, theory-driven, clinically validated and interpretable quantitative method to parse the biological heterogeneity of depression and anxiety. Thus, they represent a promising approach to advance precision clinical care in psychiatry. Personalized brain circuit measures quantified using a new imaging technology in 801 patients with depression and anxiety identify six biotypes with unique symptoms, behaviors and responses to different types of treatment.

To provide insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing 4503 OD cases, 4173 opioid-exposed controls, and 32,500 opioid-unexposed controls, including participants of European and African descent (EUR and AFR, respectively). Among the variants identified, rs9291211 was associated with OE (exposed vs. unexposed controls; EUR z = −5.39, p = 7.2 × 10–8). This variant regulates the transcriptomic profiles of SLC30A9 and BEND4 in multiple brain tissues and was previously associated with depression, alcohol consumption, and neuroticism. A phenome-wide scan of rs9291211 in the UK Biobank (N > 360,000) found association of this variant with propensity to use dietary supplements (p = 1.68 × 10–8). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8 (EUR + AFR z = 4.69, p = 10–6), which was previously associated with educational attainment, risk-taking behaviors, and schizophrenia. In addition, rs201123820 showed a genome-wide significant difference between OD cases and unexposed controls (AFR z = 5.55, p = 2.9 × 10–8) and a significant association with musculoskeletal disorders in the UK Biobank (p = 4.88 × 10–7). A polygenic risk score (PRS) based on a GWAS of risk-tolerance (n = 466,571) was positively associated with OD (OD vs. unexposed controls, p = 8.1 × 10–5; OD cases vs. exposed controls, p = 0.054) and OE (exposed vs. unexposed controls, p = 3.6 × 10–5). A PRS based on a GWAS of neuroticism (n = 390,278) was positively associated with OD (OD vs. unexposed controls, p = 3.2 × 10–5; OD vs. exposed controls, p = 0.002) but not with OE (p = 0.67). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls in studies of addiction.

Importance Cognitive deficits in depression have been associated with poor functional capacity, frontal neural circuit dysfunction, and worse response to conventional antidepressants. However, it is not known whether these impairments combine together to identify a specific cognitive subgroup (or “biotype”) of individuals with major depressive disorder (MDD), and the extent to which these impairments mediate antidepressant outcomes. Objective To undertake a systematic test of the validity of a proposed cognitive biotype of MDD across neural circuit, symptom, social occupational function, and treatment outcome modalities. Design, Setting, and Participants This secondary analysis of a randomized clinical trial implemented data-driven clustering in findings from the International Study to Predict Optimized Treatment in Depression, a pragmatic biomarker trial in which patients with MDD were randomized in a 1:1:1 ratio to antidepressant treatment with escitalopram, sertraline, or venlafaxine extended-release and assessed at baseline and 8 weeks on multimodal outcomes between December 1, 2008, and September 30, 2013. Eligible patients were medication-free outpatients with nonpsychotic MDD in at least the moderate range, and were recruited from 17 clinical and academic practices; a subset of these patients underwent functional magnetic resonance imaging. This prespecified secondary analysis was performed between June 10, 2022, and April 21, 2023. Main Outcomes and Measures Pretreatment and posttreatment behavioral measures of cognitive performance across 9 domains, depression symptoms assessed using 2 standard depression scales, and psychosocial function assessed using the Social and Occupational Functioning Assessment Scale and World Health Organization Quality of Life scale were analyzed. Neural circuit function engaged during a cognitive control task was measured using functional magnetic resonance imaging. Results A total of 1008 patients (571 [56.6%] female; mean [SD] age, 37.8 [12.6] years) participated in the overall trial and 96 patients participated in the imaging substudy (45 [46.7%] female; mean [SD] age, 34.5 [13.5] years). Cluster analysis identified what may be referred to as a cognitive biotype of 27% of depressed patients with prominent behavioral impairment in executive function and response inhibition domains of cognitive control. This biotype was characterized by a specific profile of pretreatment depressive symptoms, worse psychosocial functioning (d = −0.25; 95% CI, −0.39 to −0.11;P < .001), and reduced activation of the cognitive control circuit (right dorsolateral prefrontal cortex:d = −0.78; 95% CI, −1.28 to −0.27;P = .003). Remission was comparatively lower in the cognitive biotype positive subgroup (73 of 188 [38.8%] vs 250 of 524 [47.7%];P = .04) and cognitive impairments persisted regardless of symptom change (executive function:ηp2 = 0.241;P < .001; response inhibition:ηp2 = 0.750;P < .001). The extent of symptom and functional change was specifically mediated by change in cognition but not the reverse. Conclusions and Relevance Our findings suggest the presence of a cognitive biotype of depression with distinct neural correlates, and a functional clinical profile that responds poorly to standard antidepressants and instead may benefit from therapies specifically targeting cognitive dysfunction. Trial Registration ClinicalTrials.gov Identifier:NCT00693849

There is a critical need to better understand the neural basis of antidepressant medication (ADM) response with respect to both symptom alleviation and quality of life (QoL) in major depressive disorder (MDD). Reward neurocircuitry has been implicated in QoL, the neural basis of MDD, and the mechanisms of ADM response. Yet, we do not know whether change in reward neurocircuitry as a function of ADM is associated with change in symptoms and QoL. To address this gap in knowledge, we analyzed data from 128 patients with MDD who participated in the iSPOT-D trial and were assessed with functional neuroimaging pre- and post-ADM treatment (randomized to sertraline, venlafaxine-XR, or escitalopram). 58 matched healthy controls were scanned at the same time points. We quantified functional connectivity (FC) of reward neurocircuitry using nucleus accumbens (NAc) seed regions of interest, and then characterized how changes in FC relate to symptom response (primary outcome) and QoL response (secondary outcome). Symptom responders showed an increase in NAc-dorsal anterior cingulate cortex (ACC) FC relative to non-responders (p < 0.001) which was associated with improvement in physical QoL (p < 0.0003), and a decrease in NAc-inferior parietal lobule FC relative to controls (p < 0.001). QoL response was characterized by increases in FC between NAc-ventral ACC for environmental, NAc-thalamus for physical, and NAc-paracingulate gyrus for social domains (p < 0.001). Symptom responders to sertraline were distinguished by a decrease in NAc-insula FC (p < 0.001) and to venlafaxine-XR by an increase in NAc-inferior temporal gyrus FC (p < 0.005). Findings suggest that change in reward neurocircuitry may underlie differential ADM response profiles with respect to symptoms and QoL in depression.

We present the case of Mr. B, who was part of a NIMH-funded, longitudinal, observational study (2013 to 2016) that recruited unmedicated participants who were experiencing a range of palpable symptoms related to states of negative affect and who were assessed on multiple objective measures. A feedback report was generated based on Mr. B's multimodal measurements. One of the authors, LMW, along with Mr. B's psychotherapist, discussed the results with Mr. B in a feedback session. Mr. B's objective testing profile was consistent with a history of trauma, allowing him for the first time to be comfortable with revealing to his therapist that he experienced early-life trauma. Mr. B's case highlights several known advantages of integrating objective data into psychiatric encounters, including reducing stigma, motivating patients to pursue treatment, and improving clinical outcomes by aiding in identification of the right treatment, which is the ultimate goal of precision psychiatry. [Psychiatr Ann. 2024;54(4):e113–e118.]

Ketamine may have antidepressant properties, but its acute psychoactive effects complicate successful masking in placebo-controlled trials. We present a single-center, parallel-arm, triple-masked, randomized, placebo-controlled trial assessing the antidepressant efficacy of intravenous ketamine masked by surgical anesthesia (ClinicalTrials.gov, NCT03861988). Forty adult patients with major depressive disorder who were scheduled for routine surgery were randomized to a single infusion of ketamine (0.5 mg/kg) or placebo (saline) during usual anesthesia. All participants, investigators, and direct patient care staff were masked to treatment allocation. The primary outcome was depression severity measured by the Montgomery-Åsberg Depression Rating Scale (MADRS) at 1, 2, and 3 days post-infusion. After all follow-up visits, participants were asked to guess which intervention they received. A mixed-effects model showed no evidence of effect of treatment assignment on the primary outcome (-5.82, 95% CI -13.3 to 1.64, p=0.13). 36.8% of participants guessed their treatment assignment correctly; both groups allocated their guesses in similar proportions. In conclusion, a single dose of intravenous ketamine delivered during surgical anesthesia had no greater effect than placebo in acutely reducing the severity of depressive symptoms in adults with major depressive disorder. This trial successfully masked treatment allocation in moderate-to-severely depressed patients using surgical anesthesia. Although this masking strategy is impractical for most placebo-controlled trials, future studies of novel antidepressants with acute psychoactive effects should make efforts to fully mask treatment assignment in order to minimize subject-expectancy bias.

Alcohol misuse (AM) is highly prevalent and harmful, with theorized subgroups differing on internalizing and externalizing dimensions. Despite known heterogeneity, genome-wide association studies (GWAS) are usually conducted on unidimensional phenotypes. These approaches have identified important genes related to AM but fail to capture a large part of the heritability, even with recent increases in sample sizes. This study aimed to address phenotypic heterogeneity in GWAS to aid gene finding and to uncover the etiology of different types of AM. Genetic and phenotypic data from 410,414 unrelated individuals of multiple ancestry groups (primarily European) in the UK Biobank were obtained. Mixture modeling was applied to measures of alcohol misuse and internalizing/externalizing psychopathology to uncover phenotypically homogenous subclasses, which were carried forward to GWAS and functional annotation. A four-class model emerged with “low risk”, “internalizing—light/non-drinkers”, “heavy alcohol use—low impairment”, and “broad high risk” classes. SNP heritability ranged from 3 to 18% and both known AM signals and novel signals were captured by genomic risk loci. Class comparisons showed distinct patterns of regional brain tissue enrichment and genetic correlations with internalizing and externalizing phenotypes. Despite some limitations, this study demonstrated the utility of genetic research on homogenous subclasses. Not only were novel genetic signals identified that might be used for follow-up studies, but addressing phenotypic heterogeneity allows for the discovery and investigation of differential genetic vulnerabilities in the development of AM, which is an important step towards the goal of personalized medicine.