Oral esketamine in patients with treatment-resistant depression: a double-blind, randomized, placebo-controlled trial with open-label extension.

About one-third of patients with depression do not achieve adequate response to current treatment options. Although intravenous and intranasal administrations of (es)ketamine have shown antidepressant properties, their accessibility and scalability are limited. We investigated the efficacy, safety, and tolerability of generic oral esketamine in patients with treatment-resistant depression (TRD) in a randomized placebo-controlled trial with open-label extension. This study consisted of 1) a six-week fixed low-dose treatment phase during which 111 participants received oral esketamine 30 mg or placebo three times a day; 2) a four-week wash-out phase; and 3) an optional six-week open-label individually titrated treatment phase during which participants received 0.5 to 3.0 mg/kg oral esketamine two times a week. The primary outcome measure was change in depressive symptom severity, assessed with the Hamilton Depression Rating Scale (HDRS17), from baseline to 6 weeks. Fixed low-dose oral esketamine when compared to placebo had no benefit on the HDRS17 total score (p = 0.626). Except for dizziness and sleep hallucinations scores, which were higher in the esketamine arm, we found no significant difference in safety and tolerability aspects. During the open-label individually titrated treatment phase, the mean HDRS17 score decreased from 21.0 (SD 5.09) to 15.1 (SD 7.27) (mean difference -6.0, 95% CI -7.71 to -4.29, p < 0.001). Our results suggest that fixed low-dose esketamine is not effective in TRD. In contrast, individually titrated higher doses of oral esketamine might have antidepressant properties.

Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis.

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress.

The mediating role of health behaviors in the association between depression, anxiety and cancer incidence: an individual participant data meta-analysis.

BACKGROUND: Although behavioral mechanisms in the association among depression, anxiety, and cancer are plausible, few studies have empirically studied mediation by health behaviors. We aimed to examine the mediating role of several health behaviors in the associations among depression, anxiety, and the incidence of various cancer types (overall, breast, prostate, lung, colorectal, smoking-related, and alcohol-related cancers). METHODS: Two-stage individual participant data meta-analyses were performed based on 18 cohorts within the Psychosocial Factors and Cancer Incidence consortium that had a measure of depression or anxiety (N = 319 613, cancer incidence = 25 803). Health behaviors included smoking, physical inactivity, alcohol use, body mass index (BMI), sedentary behavior, and sleep duration and quality. In stage one, path-specific regression estimates were obtained in each cohort. In stage two, cohort-specific estimates were pooled using random-effects multivariate meta-analysis, and natural indirect effects (i.e. mediating effects) were calculated as hazard ratios (HRs). RESULTS: Smoking (HRs range 1.04-1.10) and physical inactivity (HRs range 1.01-1.02) significantly mediated the associations among depression, anxiety, and lung cancer. Smoking was also a mediator for smoking-related cancers (HRs range 1.03-1.06). There was mediation by health behaviors, especially smoking, physical inactivity, alcohol use, and a higher BMI, in the associations among depression, anxiety, and overall cancer or other types of cancer, but effects were small (HRs generally below 1.01). CONCLUSIONS: Smoking constitutes a mediating pathway linking depression and anxiety to lung cancer and smoking-related cancers. Our findings underline the importance of smoking cessation interventions for persons with depression or anxiety.

High-Dose Methylphenidate and Carboxylesterase 1 Genetic Variability in Patients With Attention-Deficit/Hyperactivity Disorder: A Case Series.

PURPOSE/BACKGROUND: Methylphenidate (MPH) is widely used to reduce symptoms of attention-deficit/hyperactivity disorder. Methylphenidate is metabolized by the carboxylesterase 1 (CES1) enzyme. Some patients need a very high dose of MPH to reach desired clinical effects, without having adverse effects. This may be due to differences in MPH pharmacokinetics (PK), potentially caused by DNA variants in CES1 , the gene encoding the enzyme that metabolizes MPH. Here we describe 3 patients requiring high-dose MPH and investigated the CES1 gene. METHODS/PROCEDURES: The 3 patients were using short-acting MPH in a dose of 180 to 640 mg instead of the maximum advised dose of around 100 mg MPH in the Netherlands. Plasma concentrations of MPH were determined at scheduled time points (day-curve). Methylphenidate plasma concentrations were used for PK analysis using an earlier published 2-compartment PK population model of MPH. Individual data of the 3 patients were compared with simulated population data, when equivalent doses were used. In addition, CES1 was genotyped (number of gene copies and single nucleotide polymorphisms) using real-time polymerase chain reaction. FINDINGS/RESULTS: Pharmacokinetic analysis in all 3 patients showed lower plasma concentrations of MPH in comparison with the population data. The mean absorption time and volume of distribution of the central compartment were equal, but the elimination clearance was higher. However, CES1 genotyping revealed no variations that could explain a higher metabolism of MPH. IMPLICATIONS/CONCLUSIONS: In these 3 cases, we could not demonstrate a correlation between MPH clearance and known genetic variants of the CES1 gene.

Change in brain activation after transcranial pulsed electromagnetic fields in treatment-resistant depression.

BACKGROUND: Preliminary evidence suggests antidepressant effects of transcranial pulsed electromagnetic fields (tPEMF). However, the precise mechanism of action in the brain is still unknown. The aim of this study was to investigate the influence of tPEMF on brain activation in patients with treatment-resistant depression (TRD) by studying two processes that might be of particular interest in relation to the symptoms of depression: emotional processing and reward processing. METHODS: Eligible participants (n = 50) with TRD in this sham-controlled double-blind multicenter trial [registered at the Dutch Trial Register ( http://www.trialregister.nl ), NTR3702] were randomly assigned to five weeks daily active or sham tPEMF. Pre- and post-treatment functional MR-scans were made during which participants performed a social-emotional task and a reward task. RESULTS: Participants in the active treatment group showed a stronger decrease in activation post-treatment compared to sham during reward-outcome processing in the left inferior frontal gyrus and in a cluster comprising the right lingual gyrus and the posterior part of the middle temporal gyrus. No effect of tPEMF was found on activation during the social-emotional task. Neurostimulation with tPEMF did also not affect behavioral performance for both tasks. CONCLUSIONS: We found a decrease in reward-related activation as a result of tPEMF stimulation, while no effect of tPEMF on social-emotional processing was found. The treatment-related reduction in activation of regulatory regions may reflect normalization and may have implications for anhedonia. These findings suggest that there is an effect of tPEMF on brain activation of relevant circuits, albeit in the absence of a clinical antidepressant effect.

Identifying predictors of a favourable outcome for outpatients with a persistent depressive disorder treated with Cognitive Behavioural Analysis System of Psychotherapy: A prospective cohort study.

OBJECTIVES: Cognitive Behavioural Analysis System of Psychotherapy (CBASP) is the first therapy specifically developed for persistent depressive disorder (PDD). This study aimed to identify predictors of favourable treatment outcome after group CBASP and assess change in depression severity over 24 weeks. DESIGN: A prospective cohort study was conducted in patients with PDD treated with group-CBASP. METHODS: Outcomes were depression severity measured by the Inventory of Depression Severity-self-report (IDS-SR) after 6 and 12 months. Potential predictors investigated were baseline depression severity, prior antidepressant use, age, family status, income source, age of onset and childhood trauma. Multivariate logistic regression was performed to assess their effects with a ≥25% IDS-SR score decrease as the dependent variable. RESULTS: The IDS-SR score (range 0-84) significantly decreased from 37.78 at start to 33.45 at 6 months, an improvement which was maintained at 12 months. Having paid work and no axis I comorbidity significantly predicted favourable response. In the groups without a favourable outcome predictor a substantial percentage still showed at least partial response (16.7% and 19.2%). CONCLUSIONS: Source of income and axis I comorbidity were predictors of response to group-CBASP. Within the group without favourable outcome predictors, a subgroup showed at least partial response. These results suggest that group-CBASP has promise for patients who do not respond to standard treatments. Future studies should include outcome measures that take into account comorbidity and other clinically relevant changes, such as social functioning.

Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis.

BACKGROUND: Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium. METHODS: The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2). RESULTS: No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06-1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04-1.23). CONCLUSIONS: Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers. PREREGISTRATION NUMBER: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157677.

Statistical power in clinical trials of interventions for mood, anxiety, and psychotic disorders.

BACKGROUND: Previous research has suggested that statistical power is suboptimal in many biomedical disciplines, but it is unclear whether power is better in trials for particular interventions, disorders, or outcome types. We therefore performed a detailed examination of power in trials of psychotherapy, pharmacotherapy, and complementary and alternative medicine (CAM) for mood, anxiety, and psychotic disorders. METHODS: We extracted data from the Cochrane Database of Systematic Reviews (Mental Health). We focused on continuous efficacy outcomes and estimated power to detect predetermined effect sizes (standardized mean difference [SMD] = 0.20-0.80, primary SMD = 0.40) and meta-analytic effect sizes (ESMA). We performed meta-regression to estimate the influence of including underpowered studies in meta-analyses. RESULTS: We included 256 reviews with 10 686 meta-analyses and 47 384 studies. Statistical power for continuous efficacy outcomes was very low across intervention and disorder types (overall median [IQR] power for SMD = 0.40: 0.32 [0.19-0.54]; for ESMA: 0.23 [0.09-0.58]), only reaching conventionally acceptable levels (80%) for SMD = 0.80. Median power to detect the ESMA was higher in treatment-as-usual (TAU)/waitlist-controlled (0.49-0.63) or placebo-controlled (0.12-0.38) trials than in trials comparing active treatments (0.07-0.13). Adequately-powered studies produced smaller effect sizes than underpowered studies (B = -0.06, p ⩽ 0.001). CONCLUSIONS: Power to detect both predetermined and meta-analytic effect sizes in psychiatric trials was low across all interventions and disorders examined. Consistent with the presence of reporting bias, underpowered studies produced larger effect sizes than adequately-powered studies. These results emphasize the need to increase sample sizes and to reduce reporting bias against studies reporting null results to improve the reliability of the published literature.

Antiviral treatment in schizophrenia: a randomized pilot PET study on the effects of valaciclovir on neuroinflammation.

BACKGROUND: Patients with schizophrenia experience cognitive impairment, which could be related to neuroinflammation in the hippocampus. The cause for such hippocampal inflammation is still unknown, but it has been suggested that herpes virus infection is involved. This study therefore aimed to determine whether add-on treatment of schizophrenic patients with the anti- viral drug valaciclovir would reduce hippocampal neuroinflammation and consequently improve cognitive symptoms. METHODS: We performed a double-blind monocenter study in 24 male and female patients with schizophrenia, experiencing active psychotic symptoms. Patients were orally treated with the anti-viral drug valaciclovir for seven consecutive days (8 g/day). Neuroinflammation was measured with Positron Emission Tomography using the translocator protein ligand [11C]-PK11195, pre-treatment and at seven days post-treatment, as were psychotic symptoms and cognition. RESULTS: Valaciclovir treatment resulted in reduced TSPO binding (39%) in the hippocampus, as well as in the brainstem, frontal lobe, temporal lobe, parahippocampal gyrus, amygdala, parietal lobe, occipital lobe, insula and cingulate gyri, nucleus accumbens and thalamus (31-40%) when using binding potential (BPND) as an outcome. With total distribution volume (VT) as outcome we found essentially the same results, but associations only approached statistical significance (p = 0.050 for hippocampus). Placebo treatment did not affect neuroinflammation. No effects of valaciclovir on psychotic symptoms or cognitive functioning were found. CONCLUSION: We found a decreased TSPO binding following antiviral treatment, which could suggest a viral underpinning of neuroinflammation in psychotic patients. Whether this reduced neuroinflammation by treatment with valaciclovir has clinical implications and is specific for schizophrenia warrants further research.

Prevalence of internalizing disorders, symptoms, and traits across age using advanced nonlinear models.

BACKGROUND: Most epidemiological studies show a decrease of internalizing disorders at older ages, but it is unclear how the prevalence exactly changes with age, and whether there are different patterns for internalizing symptoms and traits, and for men and women. This study investigates the impact of age and sex on the point prevalence across different mood and anxiety disorders, internalizing symptoms, and neuroticism. METHODS: We used cross-sectional data on 146 315 subjects, aged 18-80 years, from the Lifelines Cohort Study, a Dutch general population sample. Between 2012 and 2016, five current internalizing disorders - major depression, dysthymia, generalized anxiety disorder, social phobia, and panic disorder - were assessed according to DSM-IV criteria. Depressive symptoms, anxiety symptoms, neuroticism, and negative affect (NA) were also measured. Generalized additive models were used to identify nonlinear patterns across age, and to investigate sex differences. RESULTS: The point prevalence of internalizing disorders generally increased between the ages of 18 and 30 years, stabilized between 30 and 50, and decreased after age 50. The patterns of internalizing symptoms and traits were different. NA and neuroticism gradually decreased after age 18. Women reported more internalizing disorders than men, but the relative difference remained stable across age (relative risk ~1.7). CONCLUSIONS: The point prevalence of internalizing disorders was typically highest between age 30 and 50, but there were differences between the disorders, which could indicate differences in etiology. The relative gap between the sexes remained similar across age, suggesting that changes in sex hormones around the menopause do not significantly influence women's risk of internalizing disorders.

A network analysis of depressive symptoms and metabolomics.

BACKGROUND: Depression is associated with metabolic alterations including lipid dysregulation, whereby associations may vary across individual symptoms. Evaluating these associations using a network perspective yields a more complete insight than single outcome-single predictor models. METHODS: We used data from the Netherlands Study of Depression and Anxiety (N = 2498) and leveraged networks capturing associations between 30 depressive symptoms (Inventory of Depressive Symptomatology) and 46 metabolites. Analyses involved 4 steps: creating a network with Mixed Graphical Models; calculating centrality measures; bootstrapping for stability testing; validating central, stable associations by extra covariate-adjustment; and validation using another data wave collected 6 years later. RESULTS: The network yielded 28 symptom-metabolite associations. There were 15 highly-central variables (8 symptoms, 7 metabolites), and 3 stable links involving the symptoms Low energy (fatigue), and Hypersomnia. Specifically, fatigue showed consistent associations with higher mean diameter for VLDL particles and lower estimated degree of (fatty acid) unsaturation. These remained present after adjustment for lifestyle and health-related factors and using another data wave. CONCLUSIONS: The somatic symptoms Fatigue and Hypersomnia and cholesterol and fatty acid measures showed central, stable, and consistent relationships in our network. The present analyses showed how metabolic alterations are more consistently linked to specific symptom profiles.

A blended module (STAIRS) to promote functional and personal recovery in patients with a major depressive disorder in remission: study protocol of a concurrent mixed methods randomized controlled trial.

BACKGROUND: Despite the availability of a wide variety of evidence-based treatments for major depressive disorder (MDD), many patients still experience impairments in their lives after remission. Programs are needed that effectively support patients in coping with these impairments. The program Storytelling and Training to Advance Individual Recovery Skills (STAIRS) was developed to address this need and combines the use of peer contact, expert-by-experience guidance, family support and professional blended care. The aim of the planned study is (1) to assess the efficacy of the STAIRS program in patients with remitted MDD, (2) to investigate patients' subjective experiences with STAIRS, and (3) to evaluate the program's cost-effectiveness. METHODS: A concurrent mixed-methods randomized controlled trial design will be used. Patients aged between 18 and 65 years with remitted MDD (N = 140) will be randomized to either a group receiving care as usual (CAU) + the STAIRS-program or a control group receiving CAU + some basic psychoeducation. Quantitative efficacy data on functional and personal recovery and associated aspects will be collected using self-report questionnaires at the start of the intervention, immediately following the intervention, and at the six-month follow-up. Insights into patients' experiences on perceived effects and the way in which different program elements contribute to this effect, as well as the usability and acceptability of the program, will be gained by conducting qualitative interviews with patients from the experimental group, who are selected using maximum variation sampling. Finally, data on healthcare resource use, productivity loss and quality of life will be collected and analysed to assess the cost-effectiveness and cost-utility of the STAIRS-program. DISCUSSION: Well-designed recovery-oriented programs for patients suffering from MDD are scarce. If efficacy and cost-effectiveness are demonstrated with this study and patients experience the STAIRS program as usable and acceptable, this program can be a valuable addition to CAU. The qualitative interviews may give insights into what works for whom, which can be used to promote implementation. TRIAL REGISTRATION: This trial was registered at ClinicalTrials.gov on 1 July 2021, registration number NCT05440812.

The Relationship between Insomnia and the Pathophysiology of Major Depressive Disorder: An Evaluation of a Broad Selection of Serum and Urine Biomarkers.

Insomnia exhibits a clinically relevant relationship with major depressive disorder (MDD). Increasing evidence suggests that insomnia is associated with neurobiological alterations that resemble the pathophysiology of MDD. However, research in a clinical population is limited. The present study, therefore, aimed to investigate the relationship between insomnia and the main pathophysiological mechanisms of MDD in a clinical sample of individuals with MDD. Data were extracted from three cohorts (N = 227) and included an evaluation of depression severity (Quick Inventory of Depressive Symptomatology, QIDS-SR16) and insomnia severity (QIDS-SR16 insomnia items) as well as serum and urine assessments of 24 immunologic (e.g., tumour necrosis factor α receptor 2 and calprotectin), neurotrophic (e.g., brain-derived neurotrophic factor and epidermal growth factor), neuroendocrine (e.g., cortisol and aldosterone), neuropeptide (i.e., substance P), and metabolic (e.g., leptin and acetyl-L-carnitine) biomarkers. Linear regression analyses evaluating the association between insomnia severity and biomarker levels were conducted with and without controlling for depression severity (M = 17.32), antidepressant use (18.9%), gender (59.0% female; 40.5% male), age (M = 42.04), and the cohort of origin. The results demonstrated no significant associations between insomnia severity and biomarker levels. In conclusion, for the included biomarkers, current findings reveal no contribution of insomnia to the clinical pathophysiology of MDD.

Investigating data-driven biological subtypes of psychiatric disorders using specification-curve analysis.

BACKGROUND: Cluster analyses have become popular tools for data-driven classification in biological psychiatric research. However, these analyses are known to be sensitive to the chosen methods and/or modelling options, which may hamper generalizability and replicability of findings. To gain more insight into this problem, we used Specification-Curve Analysis (SCA) to investigate the influence of methodological variation on biomarker-based cluster-analysis results. METHODS: Proteomics data (31 biomarkers) were used from patients (n = 688) and healthy controls (n = 426) in the Netherlands Study of Depression and Anxiety. In SCAs, consistency of results was evaluated across 1200 k-means and hierarchical clustering analyses, each with a unique combination of the clustering algorithm, fit-index, and distance metric. Next, SCAs were run in simulated datasets with varying cluster numbers and noise/outlier levels to evaluate the effect of data properties on SCA outcomes. RESULTS: The real data SCA showed no robust patterns of biological clustering in either the MDD or a combined MDD/healthy dataset. The simulation results showed that the correct number of clusters could be identified quite consistently across the 1200 model specifications, but that correct cluster identification became harder when the number of clusters and noise levels increased. CONCLUSION: SCA can provide useful insights into the presence of clusters in biomarker data. However, SCA is likely to show inconsistent results in real-world biomarker datasets that are complex and contain considerable levels of noise. Here, the number and nature of the observed clusters may depend strongly on the chosen model-specification, precluding conclusions about the existence of biological clusters among psychiatric patients.

Predicting the naturalistic course in anxiety disorders using clinical and biological markers: a machine learning approach.

BACKGROUND: Disease trajectories of patients with anxiety disorders are highly diverse and approximately 60% remain chronically ill. The ability to predict disease course in individual patients would enable personalized management of these patients. This study aimed to predict recovery from anxiety disorders within 2 years applying a machine learning approach. METHODS: In total, 887 patients with anxiety disorders (panic disorder, generalized anxiety disorder, agoraphobia, or social phobia) were selected from a naturalistic cohort study. A wide array of baseline predictors (N = 569) from five domains (clinical, psychological, sociodemographic, biological, lifestyle) were used to predict recovery from anxiety disorders and recovery from all common mental disorders (CMDs: anxiety disorders, major depressive disorder, dysthymia, or alcohol dependency) at 2-year follow-up using random forest classifiers (RFCs). RESULTS: At follow-up, 484 patients (54.6%) had recovered from anxiety disorders. RFCs achieved a cross-validated area-under-the-receiving-operator-characteristic-curve (AUC) of 0.67 when using the combination of all predictor domains (sensitivity: 62.0%, specificity 62.8%) for predicting recovery from anxiety disorders. Classification of recovery from CMDs yielded an AUC of 0.70 (sensitivity: 64.6%, specificity: 62.3%) when using all domains. In both cases, the clinical domain alone provided comparable performances. Feature analysis showed that prediction of recovery from anxiety disorders was primarily driven by anxiety features, whereas recovery from CMDs was primarily driven by depression features. CONCLUSIONS: The current study showed moderate performance in predicting recovery from anxiety disorders over a 2-year follow-up for individual patients and indicates that anxiety features are most indicative for anxiety improvement and depression features for improvement in general.

Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses.

BACKGROUND: Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease. METHODS: We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions. RESULTS: We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (- 0.08 standard deviation (SD)[95% confidence interval (CI) - 0.12, - 0.03] in AMV and - 0.03SD [- 0.07, - 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (- 0.04SD [- 0.08, 0.00] in AMV and - 0.05SD [- 0.09, - 0.02] in MR), and lower phospholipids in very large HDL particles (- 0.04SD [- 0.08, 0.002] in AMV and - 0.05SD [- 0.08, - 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures. CONCLUSIONS: Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.

Pharmacodynamic Interactions Between Ketamine and Psychiatric Medications Used in the Treatment of Depression: A Systematic Review.

BACKGROUND: The use of ketamine for depression has increased rapidly in the past decades. Ketamine is often prescribed as an add-on to other drugs used in psychiatric patients, but clear information on drug-drug interactions is lacking. With this review, we aim to provide an overview of the pharmacodynamic interactions between ketamine and mood stabilizers, benzodiazepines, monoamine oxidase-inhibitors, antipsychotics, and psychostimulants. METHODS: MEDLINE and Web of Science were searched. RESULTS: Twenty-four studies were included. For lithium, no significant interactions with ketamine were reported. Two out of 5 studies on lamotrigine indicated that the effects of ketamine were attenuated. Benzodiazepines were repeatedly shown to reduce the duration of ketamine's antidepressant effect. For the monoamine oxidase-inhibitor tranylcypromine, case reports showed no relevant changes in vital signs during concurrent S-ketamine use. One paper indicated an interaction between ketamine and haloperidol, 2 other studies did not. Four papers investigated risperidone, including 3 neuroimaging studies showing an attenuating effect of risperidone on ketamine-induced brain perfusion changes. Clozapine significantly blunted ketamine-induced positive symptoms in patients with schizophrenia but not in healthy participants. One paper reported no effect of olanzapine on ketamine's acute psychotomimetic effects. CONCLUSION: Current literature shows that benzodiazepines and probably lamotrigine reduce ketamine's treatment outcome, which should be taken into account when considering ketamine treatment. There is evidence for an interaction between ketamine and clozapine, haloperidol, and risperidone. Due to small sample sizes, different subject groups and various outcome parameters, the evidence is of low quality. More studies are needed to provide insight into pharmacodynamic interactions with ketamine.

Fractal biomarker of activity in patients with bipolar disorder.

BACKGROUND: The output of many healthy physiological systems displays fractal fluctuations with self-similar temporal structures. Altered fractal patterns are associated with pathological conditions. There is evidence that patients with bipolar disorder have altered daily behaviors. METHODS: To test whether fractal patterns in motor activity are altered in patients with bipolar disorder, we analyzed 2-week actigraphy data collected from 106 patients with bipolar disorder type I in a euthymic state, 73 unaffected siblings of patients, and 76 controls. To examine the link between fractal patterns and symptoms, we analyzed 180-day actigraphy and mood symptom data that were simultaneously collected from 14 patients. RESULTS: Compared to controls, patients showed excessive regularity in motor activity fluctuations at small time scales (<1.5 h) as quantified by a larger scaling exponent (α1 > 1), indicating a more rigid motor control system. α1 values of siblings were between those of patients and controls. Further examinations revealed that the group differences in α1 were only significant in females. Sex also affected the group differences in fractal patterns at larger time scales (>2 h) as quantified by scaling exponent α2. Specifically, female patients and siblings had a smaller α2 compared to female controls, indicating more random activity fluctuations; while male patients had a larger α2 compared to male controls. Interestingly, a higher weekly depression score was associated with a lower α1 in the subsequent week. CONCLUSIONS: Our results show sex- and scale-dependent alterations in fractal activity regulation in patients with bipolar disorder. The mechanisms underlying the alterations are yet to be determined.

The association between plasma tryptophan catabolites and depression: The role of symptom profiles and inflammation.

BACKGROUND: Tryptophan catabolites ("TRYCATs") produced by the kynurenine pathway (KP) may play a role in depression pathophysiology. Studies comparing TRYCATs levels in depressed subjects and controls provided mixed findings. We examined the association of TRYCATs levels with 1) the presence of Major Depressive Disorder (MDD), 2) depressive symptom profiles and 3) inflammatory markers. METHODS: The sample from the Netherlands Study of Depression and Anxiety included participants with current (n = 1100) or remitted (n = 753) MDD DSM-IV diagnosis and healthy controls (n = 642). Plasma levels of tryptophan (TRP), kynurenine (KYN), kynurenic acid (KynA), quinolinic acid (QA), C-reactive protein (CRP), interleukin-6 (IL-6) and tumor necrosis factor (TNF) were measured. Atypical/energy-related symptom (AES), melancholic symptom (MS) and anxious-distress symptom (ADS) profiles were derived from questionnaires. RESULTS: After adjustment for age, sex, education, smoking status, alcohol consumption and chronic diseases, no significant differences in TRYCATs were found comparing MDD cases versus controls. The MS profile was associated (q < 0.05) with lower KynA (ß = -0.05), while AES was associated with higher KYN (ß = 0.05), QA (ß = 0.06) and TRP (ß = 0.06). Inflammatory markers were associated with higher KYN (CRP ß = 0.12, IL-6 ß = 0.08, TNF ß = 0.10) and QA (CRP ß = 0.21, IL-6 ß = 0.12, TNF ß = 0.18). Significant differences against controls emerged after selecting MDD cases with high (top 30%) CRP (KYN d = 0.20, QA d = 0.33) and high TNF (KYN d = 0.24; QA d = 0.39). CONCLUSIONS: TRYCATs levels were related to specific clinical and biological features, such as atypical symptoms or a proinflammatory status. Modulation of KP may potentially benefit a specific subset of depressed patients. Clinical studies should focus on patients with clear evidence of KP dysregulations.

Basal and LPS-stimulated inflammatory markers and the course of anxiety symptoms.

A cross-sectional relationship between low-grade inflammation -characterized by increased blood levels of C-reactive protein (CRP) and pro-inflammatory cytokines- and anxiety has been reported, but the potential longitudinal relationship has been less well studied. We aimed to examine whether basal and lipopolysaccharide (LPS-)induced levels of inflammatory markers are associated with anxiety symptom severity over the course of nine years. We tested the association between basal and LPS-induced inflammatory markers with anxiety symptoms (measured with the Beck's Anxiety Inventory; BAI, Fear Questionnaire; FQ and Penn's State Worry Questionnaire; PSWQ) at 5 assessment waves over a period up nine years. We used multivariate-adjusted mixed models in up to 2867 participants of the Netherlands Study of Depression and Anxiety (NESDA). At baseline, 43.6% of the participants had a current anxiety disorder, of which social phobia (18.5%) was most prevalent. Our results demonstrated that baseline inflammatory markers were significantly associated with several outcomes of anxiety at baseline over nine subsequent years. BAI subscale of somatic (arousal) symptoms of anxiety, and FQ subscale of agoraphobia demonstrated the strongest effects with standardized beta-coefficients of up to 0.14. The associations were attenuated by 25%-30% after adjusting for the presence of (comorbid) major depressive disorder (MDD), but remained statistically significant. In conclusion, we found that participants with high levels of inflammatory markers have on average high levels of anxiety consisting of physical arousal and agoraphobia, which tended to persist over a period of nine years, albeit with small effect sizes. These associations were partly driven by co-morbid depression.