Search

The individual and societal factors influencing long-term recreational exercise participation during the transition from adolescence to young adulthood are not well explored. We modelled latent longitudinal recreational exercise trajectories spanning 8 years from age 16 to 24, and examined demographic, socioeconomic, behavioural, academic, and psychological predictors at age 15 of trajectory-group membership. We also explored whether trajectories were associated with health, mental health, and educational achievement at age 25. Finite mixture modelling was conducted with population-based longitudinal cohort study data collected from 2006-2017 by the Longitudinal Survey of Australian Youth (LSAY). The study sample comprised 9,353 students (49% female) from 356 Australian schools. Self-reported recreational exercise frequency data were collected in 2007, 2008, 2009, 2011, and 2014. Longitudinal latent trajectories of reported recreational exercise participation were estimated using group-based trajectory modelling for two scenarios: daily/guideline-adherent exercise versus non-daily exercise (model 1) and exercise at least once weekly versus exercise less than once weekly (model 2). Four distinct classes of long-term recreational exercise participation were identified for each model. Model 1: guideline-adherent exercisers (17.9% of the sample), never guideline exercisers (27.5%), guideline drop-outs (15.2%) and towards guideline (39.4%). Model 2: regular weekly (69.5% of the sample), decreasing (17.4%), increasing (4.8%), and infrequent (8.3%). In both models, predictors at age 15 for lower long-term exercise participation included female gender, lower self-efficacy, sport participation and parental socioeconomic status, and higher screen-time and academic literacy. At age 25, people in the guideline-adherent exerciser trajectory (model 1) reported better general health, whereas people in the regular weekly trajectory (model 2) had better general health and reduced rates of psychological distress, were happier with life and were more optimistic for the future relative to participants from other trajectory groups. Interventions and health-promotion activities to support sustained engagement in recreational exercise should particularly address the needs of females, people with low self-efficacy, reluctant exercisers, higher academic achievers, and youth experiencing socioeconomic disadvantage.

Given the role of low-grade inflammation in the pathophysiology of major depressive disorder (MDD), anti-inflammatory strategies may improve treatment outcomes in some patients. However, it is controversial whether they can be used as adjunctive treatments and whether pre-treatment levels of inflammation can predict treatment outcomes. This study was conducted to measure the efficacy of anti-inflammatory augmentation of antidepressant treatment in MDD patients; and to investigate whether treatment response was dependent on baseline inflammation levels. This parallel-group randomised, double-blind, placebo-controlled trial was conducted at the University of Adelaide (Australia). Participants with MDD were randomised to receive vortioxetine with celecoxib or vortioxetine with placebo for six weeks, and baseline blood high sensitivity C reactive protein levels were measured. Primary outcome was change in depressive symptoms (Montgomery-Åsberg Depression Rating Scale) and secondary outcomes included change in cognition (THINC-integrated tool - Codebreaker task) and functioning (Functioning Assessment Short Test) over 6 weeks. There was no evidence of superior efficacy of celecoxib augmentation over placebo on depressive symptom severity, response and remission rates, cognition and psychosocial functioning. There was also no evidence that pre-treatment inflammation levels modified the effect of celecoxib augmentation versus placebo. This observed lack of efficacy of celecoxib add-on does not support the use of celecoxib augmentation of antidepressants in the treatment of MDD in a cohort that mostly comprises treatment-resistant individuals. Additionally, C-reactive protein may not be suitable to predict treatment selection and response in MDD. The study was registered on the Australian New Zealand Clinical Trials Registry: ACTRN12617000527369 (www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12617000527369p).

Background No biological treatment has been firmly established for the at-risk stage of psychotic disorder. In this study we aim to test if subthreshold psychotic symptoms can be effectively treated with cannabidiol (CBD), a non-psychoactive compound of the plant Cannabis sativa. The question has taken on increased importance in the wake of evidence questioning both the need and efficacy of specific pharmacological interventions in the ultra-high risk (UHR) for psychosis group. Methods Three-arm randomized controlled trial of 405 patients (135 per arm) aged 12-25 years who meet UHR for psychosis criteria. The study includes a 6-week lead-in phase during which 10% of UHR individuals are expected to experience symptom remission. Participants will receive CBD (per oral) at doses 600 or 1000 mg per day (fixed schedule) for 12 weeks. Participants in the third arm of the trial will receive matching placebo capsules. Primary outcome is severity of positive psychotic symptoms as measured by the Comprehensive Assessment of At-Risk Mental States at 12 weeks. We hypothesize that CBD will be significantly more effective than placebo in improving positive psychotic symptoms in UHR patients. All participants will also be followed up 6 months post baseline to evaluate if treatment effects are sustained. Conclusion This paper reports on the rationale and protocol of the Cannabidiol for At Risk for psychosis Youth (CanARY) study. This study will test CBD for the first time in the UHR phase of psychotic disorder.

We currently observe a disconcerting phenomenon in machine learning studies in psychiatry: While we would expect larger samples to yield better results due to the availability of more data, larger machine learning studies consistently show much weaker performance than the numerous small-scale studies. Here, we systematically investigated this effect focusing on one of the most heavily studied questions in the field, namely the classification of patients suffering from Major Depressive Disorder (MDD) and healthy controls based on neuroimaging data. Drawing upon structural MRI data from a balanced sample of N = 1868 MDD patients and healthy controls from our recent international Predictive Analytics Competition (PAC), we first trained and tested a classification model on the full dataset which yielded an accuracy of 61%. Next, we mimicked the process by which researchers would draw samples of various sizes (N = 4 to N = 150) from the population and showed a strong risk of misestimation. Specifically, for small sample sizes (N = 20), we observe accuracies of up to 95%. For medium sample sizes (N = 100) accuracies up to 75% were found. Importantly, further investigation showed that sufficiently large test sets effectively protect against performance misestimation whereas larger datasets per se do not. While these results question the validity of a substantial part of the current literature, we outline the relatively low-cost remedy of larger test sets, which is readily available in most cases.

The Pearl Darter Percina aurora is an imperiled species of fish currently only found in the Pascagoula River drainage in southern Mississippi. We tested 60 microsatellite loci identified by Illumina pair-ended sequencing. Forty of these loci were polymorphic in Pearl Darters with a mean number of alleles per locus of 11.5 and mean observed and expected heterozygosity values of 0.818 and 0.805, respectively. Eleven to 17 of these loci were also polymorphic in the closely related Channel Darter P. copelandi and Coal Darter P. brevicauda. These loci should prove useful in genetic studies associated with informing future management decisions for Pearl Darters and conservation efforts in other species of darter.

Studies have been devoted to describing the diet of D. monticola. However, knowledge of how D. monticola utilizes food resources through ontogeny remains unknown. We characterized D. monticola general dietary patterns and tested for ontogenetic diet shifts. We also inferred on juvenile recruitment patterns. We examined the stomach contents of 120 specimens ranging in size from 20 to 154 mm in standard length (SL). To infer on recruitment periodicity, we examined the size of specimens deposited in museum collections to compile size frequencies by month. We assume that the occurrence of smaller-size class categories will shed light on their recruitment time. Our results show that D. monticola is an omnivore that largely feeds on aquatic insects but also includes detritus, terrestrial material, fishes and crustaceans. Our analysis did not detect strong changes in diet through ontogeny, instead some changes were detected but mainly on the percentage of some food items included at different size category classes. In regards to the recruitment periodicity, we found younger D. monticola (20–40 mm SL) throughout most of the year, suggesting that they may be reproducing for longer periods of time than those previously reported from Honduras.

Purpose Clozapine-associated myocarditis (CAM) is a serious complication, mostly occurring in the first month of treatment. Public mental health in South Australia introduced a screening protocol in 2011 using baseline and weekly C-reactive protein and troponin. The aim of this study was to assess protocol adherence and management of cases with positive screening results. Methods We identified all patients commenced on clozapine in our area between 2012 and 2015. Those with abnormal C-reactive protein and/or troponin in the first 4 weeks of treatment were identified (potential cases). For those, we collected clinical characteristics and test results and reviewed their management. Findings Protocol compliance increased to 80%. We identified 24 potential CAM cases, 8 at high risk based on established definition (7.6% of new commencements) and 9 formally diagnosed from 143 commenced on clozapine. Potential cases not meeting CAM definition were significantly more likely commenced on clozapine for the first time and have preexisting respiratory disease. Likely CAM cases were younger, and more often prescribed additional antipsychotics, specifically quetiapine. Seven (78%) of 9 patients diagnosed with CAM met published CAM definition. In 14 undiagnosed potential cases, 10 (71%) did not have timely testing to exclude CAM. Conclusions Maintaining a high index of suspicion, clinical monitoring and timely testing is important to supplement CAM screening protocols. More research is needed to identify those that can be safely rechallenged or even continue clozapine treatment with monitoring.

Understanding the genomic architecture and molecular mechanisms of cognitive functioning in healthy individuals is critical for developing tailored interventions to enhance cognitive functioning, as well as for identifying targets for treating impaired cognition. There has been substantial progress in uncovering the genetic composition of the general cognitive ability (g). However, there is an ongoing debate whether executive functioning (EF)–another key predictor of cognitive health and performance, is separable from general g. To provide an analytical review on existing findings on genetic influences on the relationship between g and EF, we re-analysed a subset of genome-wide association studies (GWAS) from the GWAS catalogue that used measures of g and EF as outcomes in non-clinical populations. We identified two sets of single nucleotide polymorphisms (SNPs) associated with g (1,372 SNPs across 12 studies), and EF (300 SNPs across 5 studies) at p-6. A comparative analysis of GWAS-identified g and EF SNPs in high linkage disequilibrium (LD), followed by pathway enrichment analyses suggest that g and EF are overlapping but separable at genetic variant and molecular pathway levels, however more evidence is required to characterize the genetic overlap/distinction between the two constructs. While not without limitations, these findings may have implications for navigating further research towards translatable genetic findings for cognitive remediation, enhancement, and augmentation.

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium’s therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.

IntroductionThere are no well-established biomedical treatments for the core symptoms of autism spectrum disorder (ASD). A small number of studies suggest that repetitive transcranial magnetic stimulation (rTMS), a non-invasive brain stimulation technique, may improve clinical and cognitive outcomes in ASD. We describe here the protocol for a funded multicentre randomised controlled clinical trial to investigate whether a course of rTMS to the right temporoparietal junction (rTPJ), which has demonstrated abnormal brain activation in ASD, can improve social communication in adolescents and young adults with ASD.Methods and analysisThis study will evaluate the safety and efficacy of a 4-week course of intermittent theta burst stimulation (iTBS, a variant of rTMS) in ASD. Participants meeting criteria for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition ASD (n=150, aged 14–40 years) will receive 20 sessions of either active iTBS (600 pulses) or sham iTBS (in which a sham coil mimics the sensation of iTBS, but no active stimulation is delivered) to the rTPJ. Participants will undergo a range of clinical, cognitive, epi/genetic, and neurophysiological assessments before and at multiple time points up to 6 months after iTBS. Safety will be assessed via a structured questionnaire and adverse event reporting. The study will be conducted from November 2020 to October 2024.Ethics and disseminationThe study was approved by the Human Research Ethics Committee of Monash Health (Melbourne, Australia) under Australia’s National Mutual Acceptance scheme. The trial will be conducted according to Good Clinical Practice, and findings will be written up for scholarly publication.Trial registration numberAustralian New Zealand Clinical Trials Registry (ACTRN12620000890932).

Objective:Impairment in psychosocial function is common in schizophrenia. Long-acting injectable atypical antipsychotics are thought to enhance psychosocial function by boosting adherence. However, no systematic review has examined the effects of long-acting injectable atypical antipsychotics on psychosocial function in clinical trials.Methods:We searched major databases including Medline/PubMed, PsychINFO, EMBASE, CINAHL, Scopus, Web of Science, Cochrane Central Register of Controlled Trials and Clinical Trial Registries for randomised controlled trials that compared long-acting injectable atypical antipsychotics to placebo, oral antipsychotic medications or long-acting injectable atypical antipsychotics for all years till 2018, with no language limits. We performed a systematic review of findings on change in psychosocial function and its predictors in the included reports. Data on change in psychosocial functioning were meta-analysed using a random-effects model.Results:A total of 26 studies were included in systematic review, and 19 studies with 8616 adults, 68.1% males were meta-analysed. Long-acting injectable atypical antipsychotics were superior to placebo (standardised mean difference = 0.39; 95% confidence interval = [0.32, 0.47]; p 2 = 0%; 9 studies) and oral antipsychotic medications (standardised mean difference = 0.16; 95% confidence interval = [0.01, 0.31]; p = 0.04; I2 = 77%; 10 studies) for improved psychosocial function and superiority was maintained in short- and long trials. Poor psychosocial function was predicted by longer treatment duration, severe symptoms, poor cognition and poor insight. Functioning was assessed by either a single or a combination of measures, but was not the primary outcome in most studies. Other sources of bias include poor blinding and reporting of randomisation.Conclusion:Long-acting injectable atypical antipsychotics are beneficial for recovery of psychosocial function in comparison with placebo, but the magnitude of superiority over oral antipsychotic treatment was small. Severe psychopathology at baseline predicted poor psychosocial function. Future effectiveness trials in which post-randomisation involvement is kept to a minimum, and psychosocial function is included as primary outcome a priori, are needed to capture the real-world impact of long-acting injectable atypical antipsychotics and to address methodological biases.

BackgroundStudying the phenotypic and genetic characteristics of age and polarity at onset (AAO, PAO) in bipolar disorder (BD) can provide new insights into disease pathology and facilitate the development of screening tools.AimsTo examine the genetic architecture of AAO and PAO and their association with BD disease characteristics.MethodsGenome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (N=12977) and PAO (N=6773) were conducted in BD patients of 34 cohorts and a replication sample (N=2237). The association of onset with disease characteristics was investigated in two of these cohorts.ResultsEarlier AAO was associated with an increased risk of psychotic symptoms, suicidality, and fewer episodes. A depressive onset correlated with lifetime suicidality and a manic onset with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in SNV-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased polygenic scores for autism spectrum disorder (β=-0.34 years, SE=0.08), major depression (β=-0.34 years, SE=0.08), schizophrenia (β=-0.39 years, SE=0.08), and educational attainment (β=-0.31 years, SE=0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.ConclusionsAAO and PAO are associated with indicators of BD severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents, and phenotype definitions introduce significant heterogeneity, affecting analyses.RELEVANCE STATEMENTIn the largest study to systematically characterize age at onset (N=12977) and polarity at onset (N=6773) in bipolar disorder, we describe an association between illness onset characteristics and indicators of severity, confirming their clinical relevance. Our study shows that that early illness onset is associated with genetic liability for a broad range of psychiatric disorders. However, we also highlight systematic differences in age at onset across cohorts, continents, and phenotype definitions. This heterogeneity results in reduced heritability and affects genetic analyses, underscoring the need for the development of standardized phenotype definitions.

Radiation therapy is a primary treatment modality for many forms of cancer. Normally, the highest tolerable dose of ionizing radiation is used to treat tumors, but limitations imposed by normal tissue complications present challenges for local tumor control. In light of this, a class of compounds called radio-sensitizers have been developed to enhance the effectiveness of radiation. Many of these are small molecule drugs found to interact favorably with radiation therapy, but recent advances have been made using nanoparticles as radio-sensitizers. Herein, we report the utilization of radio-luminescent calcium tungstate nanoparticles that emit photoelectrons, UV-A, and visible light during X-ray irradiation, acting as effective radio-sensitizers ("Radio Luminescence Therapy"). In addition, a folic acid-functionalized form of these nanoparticles was shown to enhance radio-sensitization in vitro and in murine models of head and neck cancer. Folic acid-functionalized particles were found to decrease UV-A-induced clonogenic cell survival relative to nonfunctionalized particles. Several possible mechanisms were explored, and the folic acid-functionalized particles were found to mediate this increase in efficacy likely by activating pro-proliferative signaling through folate's innate mitogenic activity, leading to decreased repair of UV-A-induced DNA lesions. Finally, a clinical case study of a canine sarcoma patient demonstrated the initial safety and feasibility of translating these folic acid-functionalized particles into the clinic as radio-sensitizers in the treatment of spontaneous tumors.

Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = −0.14; 95% confidence interval [CI]: −0.24 to −0.03; p value = 0.010) and MDD (β = −0.16; 95% CI: −0.27 to −0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34–1.93; p value = 2e−7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD.

We compliment the authors and journal for ensuring the “Consensus statement on the use of clozapine during the COVID-19 pandemic” was published in a timely fashion. Coronavirus disease 2019 (COVID-19) rapidly transformed into a pandemic, challenging medicine in ways initially not imagined; this is certainly the case not only for treatmentresistant schizophrenia and for reasons related to clozapine, but also the patient population.

In adolescents and young adults, depressive symptoms are highly prevalent and dynamic. For clinicians, it is difficult to determine whether a young person reporting depressive symptoms is at risk of developing ongoing mood difficulties, or whether symptoms form part of a transient maturational process. Hence, giving personalized treatment recommendations is a challenge in this group; current clinical practice guidelines promote a “watch and wait” approach, where generic and low-level treatments are offered first, while more intensive therapies, such as medication, are reserved for cases who do not benefit from first-line interventions. Trajectory analyses of longitudinally assessed symptoms in large cohorts have the potential to untangle clinical heterogeneity by determining subgroups or classes of symptom courses and their risk factors. Further, they explore the impact of known or suspected risk factors on a trajectory slope and intercept, and can trace the interrelation between depressive symptoms and other clinical outcomes over time. These studies suggest that young people fall into common mood trajectory classes, and that class membership and symptom course are mediated by biological and environmental risk factors. Studies also provide evidence that high and persistent depressive symptoms are associated with a range of concurrent health- and behavioral outcomes. These findings could assist in informing personalized and preventive strategies for clinical practice.

Outcomes for people with mental illness are difficult to predict due to the syndromal nature of diagnosis and the complex relationships among clinical and biological predictors and outcomes. Due to the small amounts of variance explained by individual predictors, the application of multivariate modeling techniques is key to improving the accuracy of outcome prediction. The combination of data from multiple modes of clinical and biological assessment shows potential to increase the accuracy of such models. Superior performance may be achieved by combining clinical data with imaging, electrophysiology, and blood-based biomarkers. Multimodal multivariate modeling techniques are central to the development of personalized psychiatry, affording the potential for patient stratification and individual outcome prediction. This chapter outlines the range of multimodal data available, study design, and modeling techniques.

The natural history of psychotic illness is one of fluctuating symptoms and functions, from prodromal illness, to first episode, to episodic relapse, and recovery or chronic illness. Recent evidence suggests that complex biological, symptomatic, and functional trajectory patterns underlie clinical presentations and outcomes. Statistical techniques for the analysis of longitudinal data have evolved to provide better estimates of trends and the determinants of growth and change for individual patients. The analysis of complex multimodal trajectories may be key to the personalization of psychosis treatment. This chapter will discuss the advantages and disadvantages of trajectory modeling techniques for psychosis research.

Lithium is the first-line treatment for bipolar affective disorder (BPAD) but two-thirds of patients respond only partially or not at all. The reasons for this high variability in lithium response are not well understood. Transcriptome-wide profiling, which tests the interface between genes and the environment, represents a viable means of exploring the molecular mechanisms underlying lithium response variability. Thus, in the present study we performed co-expression network analyses of whole-blood-derived RNA-seq data from n = 50 lithium-treated BPAD patients. Lithium response was assessed using the well-validated ALDA scale, which we used to define both a continuous and a dichotomous measure. We identified a nominally significant correlation between a co-expression module comprising 46 genes and lithium response represented as a continuous (i.e., scale ranging 0–10) phenotype (cor = −0.299, p = 0.035). Forty-three of these 46 genes had reduced mRNA expression levels in better lithium responders relative to poorer responders, and the central regulators of this module were all mitochondrially-encoded (MT-ND1, MT-ATP6, MT-CYB). Accordingly, enrichment analyses indicated that genes involved in mitochondrial functioning were heavily over-represented in this module, specifically highlighting the electron transport chain (ETC) and oxidative phosphorylation (OXPHOS) as affected processes. Disrupted ETC and OXPHOS activity have previously been implicated in the pathophysiology of BPAD. Our data adds to previous evidence suggesting that a normalisation of these processes could be central to lithium’s mode of action, and could underlie a favourable therapeutic response.

In order to accelerate the understanding of pathophysiological mechanisms and clinical biomarker discovery and in psychiatry, approaches that integrate multiple -omics platforms are needed. We introduce a workflow that investigates a narrowly defined psychiatric phenotype, makes use of the potent and cost-effective discovery technology of gene expression microarrays, applies Weighted Gene Co-Expression Network Analysis (WGCNA) to better capture complex and polygenic traits, and finally explores gene expression findings on the proteomic level using targeted mass-spectrometry (MS) technologies. To illustrate the effectiveness of the workflow, we present a proteomic analysis of peripheral blood plasma from patient's remitted major depressive disorder (MDD) who experience ongoing cognitive deficits. We show that co-expression patterns previous detected on the transcript level could be replicated for plasma proteins, as could the module eigengene correlation with cognitive performance. Further, we demonstrate that functional analysis of multi-omics data has the potential to point to cellular mechanisms and candidate biomarkers for cognitive dysfunction in MDD, implicating cell cycle regulation by cyclin D3 (CCND3), regulation of protein processing in the endoplasmatic reticulum by Thioredoxin domain-containing protein 5 (TXND5), and modulation of inflammatory cytokines by Tripartite Motif Containing 26 (TRI26). Significance: This paper discusses how data from multiple -omics platforms can be integrated to accelerate biomarker discovery in psychiatry. Using the phenotype of cognitive impairment in remitted major depressive disorder (MDD) as an example, we show that the application of a systems biology approach - weighted gene co-expression network analysis (WGCNA) - in the discovery phase, and targeted proteomic follow-up of results, provides a structured avenue towards uncovering novel candidate markers and pathways for personalized clinical psychiatry. Refereed/Peer-reviewed

Clozapine has unique efficacy for symptoms in treatment-resistant schizophrenia; however, symptomatic remission is not necessary nor sufficient for functional improvement. No study has pooled the effect of clozapine on psychosocial function across clinical trials. We conducted a systematic review and meta-analysis to compare the effects of clozapine with other antipsychotics on psychosocial function, and described the predictors of functional outcome. We searched MEDLINE/PubMed, PsychINFO, EMBASE, CINAHL, Scopus, Web of Science, Cochrane Central Register of controlled trials and clinical trial registries till April 2018, with no language limits. Eligible studies were randomised controlled trials of clozapine vs. typical or atypical antipsychotics among adults with treatment-resistant schizophrenia. We included studies with flexible or fixed doses of antipsychotics within the therapeutic range to reflect naturalistic care. Effect sizes of studies were pooled using generic inverse variance and random-effects models and presented as standard mean differences. Study quality was assessed in accordance with the Cochrane Collaboration guideline, and subgroup analyses were carried out to identify potential moderators and methodological biases. Nine studies with 1279 participants (69.7% male) were included. Clozapine showed beneficial effects on psychosocial function, but both short-term trials [n = 3; comparing 99 people taking clozapine with 97 controls (standardised mean difference = 0.04; 95% confidence interval − 0.24, 0.32; p = 0.77; I2 = 0%)] and long-term trials [n = 5; comparing 415 people taking clozapine with 427 controls (standardised mean difference = 0.05; 95% confidence interval − 0.16, 0.27; p = 0.64; I2 = 50%)] showed no superiority of clozapine to other antipsychotics in this regard. Only one study explored the predictors of psychosocial function. Baseline severity of illness, illicit drug use, extrapyramidal side effects, sex and cognition explained the variability in functional outcome. A range of scales measured psychosocial function, and the quality of reporting varied across trials. Clozapine does not appear superior to other antipsychotics for improvement of psychosocial function. Standardisation of psychosocial function measurement is needed to improve the quality of evidence. Further exploration of the predictors of good psychosocial outcomes with clozapine treatment may improve personalisation of care.

OBJECTIVES: Bipolar disorder (BD) with early disease onset is associated with an unfavorable clinical outcome and constitutes a clinically and biologically homogenous subgroup within the heterogeneous BD spectrum. Previous studies have found an accumulation of early age at onset (AAO) in BD families and have therefore hypothesized that there is a larger genetic contribution to the early-onset cases than to late onset BD. To investigate the genetic background of this subphenotype, we evaluated whether an increased polygenic burden of BD- and schizophrenia (SCZ)-associated risk variants is associated with an earlier AAO in BD patients. METHODS: A total of 1995 BD type 1 patients from the Consortium of Lithium Genetics (ConLiGen), PsyCourse and Bonn-Mannheim samples were genotyped and their BD and SCZ polygenic risk scores (PRSs) were calculated using the summary statistics of the Psychiatric Genomics Consortium as a training data set. AAO was either separated into onset groups of clinical interest (childhood and adolescence [≤18 years] vs adulthood [>18 years]) or considered as a continuous measure. The associations between BD- and SCZ-PRSs and AAO were evaluated with regression models. RESULTS: BD- and SCZ-PRSs were not significantly associated with age at disease onset. Results remained the same when analyses were stratified by site of recruitment. CONCLUSIONS: The current study is the largest conducted so far to investigate the association between the cumulative BD and SCZ polygenic risk and AAO in BD patients. The reported negative results suggest that such a polygenic influence, if there is any, is not large, and highlight the importance of conducting further, larger scale studies to obtain more information on the genetic architecture of this clinically relevant phenotype. peerReviewed

The southeastern United States represents one of the richest collections of aquatic biodiversity worldwide; however, many of these taxa are under an increasing threat of imperilment, local extirpation, or extinction. The pearl darter Percina aurora is a small-bodied freshwater fish endemic to the Pearl and Pascagoula river systems of Mississippi and Louisiana (USA). The last collected specimen from the Pearl River drainage was taken in 1973, and it now appears that populations in this system are likely extirpated. This reduced the historical range of this species by approximately 50%, ultimately resulting in federal protection under the US Endangered Species Act in 2017. To better understand the current distribution and general biology of extant populations, we analyzed data collected from a series of surveys conducted in the Pascagoula River drainage from 2000 to 2016. Pearl darters were captured at relatively low abundance (2.4 ± 4.0 ind. per collection) from 57% of 308 collections. We identified strong relationships between local habitat variables and occurrence and catch-per-unit-effort (CPUE) of pearl darters. Pearl darters were frequently encountered and in greater abundance in depositional areas characterized by low-velocity habitats and finer substrates. Patterns of occurrence and CPUE were spatiotemporally variable across years; however, repeated collections from a subset of localities collected across a decade or more indicated long-term persistence and stability, suggesting population resilience throughout the Pascagoula River drainage.

Clozapine is the most effective anti-psychotic medication for treatment refractory schizophrenia. A growing number of case reports have linked infection to high clozapine levels and associated adverse outcomes. We present a systematic review of published cases to clarify the relationship between infection and elevated clozapine levels. The case reports were located through PubMed and Embase. In addition, 8 new cases from two Australian states were included. Demographics, psychiatric diagnoses and medical morbidities, medications, clinical symptoms, clozapine levels, inflammatory markers and final clinical outcome were extracted. 40 cases were identified in 23 publications that demonstrated elevated clozapine levels associated with infection. Infections were commonly respiratory in origin. Adverse events, typically sedation, were associated with raised clozapine levels during infection. In many cases the signs of infection such as fever and white blood cell count were reduced. Severe adverse effects were uncommon, with one case each of seizure, myocarditis and neutropenia. The relationship between infection, clozapine levels and adverse events is complex and multi-factorial. Monitoring of clozapine levels is essential during hospitalisation for infection and consideration should be given to gradual dose reduction to minimise dose related side effects.

Clozapine is the most effective medication for treatment-refractory schizophrenia; however, its use is contraindicated in people who have had previous clozapine-induced neutropenia. Co-prescription of granulocyte-colony stimulating factor may prevent recurrent neutropenia and allow continuation or rechallenge of clozapine.Systematic review of literature reporting the use of granulocyte-colony stimulating factor to allow rechallenge or continuation of clozapine in people with previous episodes of clozapine-induced neutropenia. The efficacy of granulocyte-colony stimulating factor and predictors of successful rechallenge will be determined to elucidate whether evidence-based recommendations can be made regarding the use of granulocyte-colony stimulating factor in this context.A total of 17 articles were identified that reported on clozapine rechallenge with granulocyte-colony stimulating factor support. In all, 76% of cases were able to continue clozapine at median follow-up of 12 months. There were no clear clinical or laboratory predictors of successful rechallenge; however, initial neutropenia was more severe in successful cases compared to unsuccessful cases. Cases co-prescribed lithium had lower success rates of rechallenge (60%) compared to those who were not prescribed lithium (81%). The most commonly reported rechallenge strategy was use of filgrastim 150-480 µg between daily to three times a week. There were no medication-specific side effects of granulocyte-colony stimulating factor reported apart from euphoria in one case. Three cases who failed granulocyte-colony stimulating factor had bacterial infection at time of recurrent neutropenia. No deaths were reported.Preliminary data suggest granulocyte-colony stimulating factor is safe and effective in facilitating rechallenge with clozapine. Clinical recommendations for use are discussed.

Objective: In adolescents and young adults, depressive symptoms are highly prevalent and dynamic. For clinicians, it is difficult to determine whether a young person reporting depressive symptoms is at risk of developing ongoing mood difficulties or whether symptoms form part of a transient maturational process. Trajectory analyses of longitudinally assessed symptoms in large cohorts have the potential to untangle clinical heterogeneity by determining subgroups or classes of symptom course and their risk factors, by interrogating the impact of known or suspected risk factors on trajectory slope and intercept and by tracing the interrelation between depressive symptoms and other clinical outcomes over time. Method: We conducted a systematic review of trajectory studies conducted in cohorts including people aged between 15 and 25 years. Results: We retrieved 47 relevant articles. These studies suggest that young people fall into common mood trajectory classes and that class membership and symptom course are mediated by biological and environmental risk factors. Furthermore, studies provide evidence that high and persistent depressive symptoms are associated with a range of concurrent health and behavioral outcomes. Conclusion: Findings could assist in the formulation of novel concepts of depressive disorders in young people and inform preventive strategies and predictive models for clinical practice.

With the ongoing coronavirus disease 2019 (COVID-19) pandemic, psychiatrists find themselves in the clinical situation of being asked by patients, family members and patient advocacy societies to help ensure access to clozapine as a medication critical for ongoing patient care. To provide clozapine prescribing guidance and facilitate regulatory agencies modifying laboratory monitoring and/or dispensing requirements, an expert advisory subgroup of the Treatment Response and Resistance in Psychosis working group developed the following background, recommendations and rationale as a consensus statement.

Background: Currently, clinicians have no validated decision support systems to predict rehospitalization risk in major depressive disorder upon initial patient hospital admission. Methods: The BiDirect study is an ongoing 12-year study, integrating three cohorts, patients with depression, population controls and patients with an acute coronary event. 380 patients aged ≥ 35 and < 66 years, with a current or recent hospitalisation for a major depressive episode (Rehospitalized: yes = 102, no = 278) who completed structural imaging and genetic testing were included in the study. Machine learning models trained with baseline data from July 2010 to June 2013 were used to predict rehospitalization within two years of an initial inpatient episode. Predictor modalities used included clinical, blood-biomarker, structural imaging, genetic (polygenic risk scores), and electrocardiography predictors. Findings: Optimal performance was achieved with a multimodal panel containing structural imaging, blood-biomarker, clinical, medication type and sleep quality predictors, attaining a test AUC of 67.74 (p = 9.99-05) in an outer 10-fold cross validation loop. After controlling for covariates in a non-penalized logistic regression model, baseline right hippocampal volume and the number of previous inpatient admissions were significantly associated with rehospitalization. Interpretation: In this analysis, our multimodal model outperformed models based on clinical variables alone, combined biomarkers and individual data modality prognostication for rehospitalization. This finding points to the potential of predictive models that combine multimodal clinical and biomarker data in the development of clinical decision support systems. Funding: The BiDirect Study is funded by the German Federal Ministry of Education and Research (BMBF, (01ER0816 and 01ER1506, and 01ER1205). Additional funding for the analysis was provided by the German Research Foundation (DFG, grant FOR2107 DA1151/5-1 and DA1151/5-2 to UD; SB-TRR58, Projects C09 and Z02), the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Munster (grant Dan3/012/17 to UD, SEED 11/18) and the Deanery of the Medical Faculty of the University of Munster. In addition, this work was supported with supercomputing resources provided by the Phoenix HPC service at the University of Adelaide. Declaration of Interest: None. Ethical Approval: The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.

Recent genome-wide association studies have demonstrated that the genetic burden associated with depression correlates with depression severity. Therefore, conducting genetic studies of patients at the most severe end of the depressive disorder spectrum, those with treatment resistant depression and who are prescribed electroconvulsive therapy (ECT), could lead to a better understanding of the genetic underpinnings of depression. Despite ECT being one of the most effective forms of treatment for severe depressive disorders, it is usually placed at the end of treatment algorithms of current guidelines. This is perhaps because ECT has controlled risk and logistical demands including use of general anaesthesia and muscle relaxants and side effects such as short-term memory impairment. Better understanding of the genetics and biology of ECT response and of cognitive side effects could lead to more personalized treatment decisions. To enhance the understanding of the genomics of severe depression and ECT response, researchers and ECT providers from around the world and from various depression or ECT networks, but not limited to, such as the Psychiatric Genomics Consortium, the Clinical Alliance and Research in ECT (CARE), and the National Network of Depression Centers (NNDC) have formed the Genetics of ECT International Consortium (Gen-ECT-ic). Gen-ECT-ic will organize the largest clinical and genetic collection to date to study the genomics of severe depressive disorders and response to ECT, aiming for 30,000 patients worldwide using a GWAS approach. At this stage it will be the largest genomic study on treatment response in depression. Retrospective data abstraction and prospective data collection will be facilitated by a uniform data collection approach that is flexible and will incorporate data from many clinical practices. Gen-ECT-ic invites all ECT providers and researchers to join its efforts.