Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.

Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.

We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.

A clinical tool to estimate the risk of treatment-resistant schizophrenia (TRS) in people with first-episode psychosis (FEP) would inform early detection of TRS and overcome the delay of up to 5 years in starting TRS medication.

To develop and evaluate a model that could predict the risk of TRS in routine clinical practice.

We used data from two UK-based FEP cohorts (GAP and AESOP-10) to develop and internally validate a prognostic model that supports identification of patients at high-risk of TRS soon after FEP diagnosis. Using sociodemographic and clinical predictors, a model for predicting risk of TRS was developed based on penalised logistic regression, with missing data handled using multiple imputation. Internal validation was undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. Interviews and focus groups with clinicians were conducted to establish clinically relevant risk thresholds and understand the acceptability and perceived utility of the model.

We included seven factors in the prediction model that are predominantly assessed in clinical practice in patients with FEP. The model predicted treatment resistance among the 1081 patients with reasonable accuracy; the model's C-statistic was 0.727 (95% CI 0.723–0.732) prior to shrinkage and 0.687 after adjustment for optimism. Calibration was good (expected/observed ratio: 0.999; calibration-in-the-large: 0.000584) after adjustment for optimism.

We developed and internally validated a prediction model with reasonably good predictive metrics. Clinicians, patients and carers were involved in the development process. External validation of the tool is needed followed by co-design methodology to support implementation in early intervention services.

Evidence suggests that cognitive subtypes exist in schizophrenia that may reflect different neurobiological trajectories. We aimed to identify whether IQ-derived cognitive subtypes are present in early-phase schizophrenia-spectrum disorder and examine their relationship with brain structure and markers of neuroinflammation.

161 patients with recent-onset schizophrenia spectrum disorder (<5 years) were recruited. Estimated premorbid and current IQ were calculated using the Wechsler Test of Adult Reading and a 4-subtest WAIS-III. Cognitive subtypes were identified with k-means clustering. Freesurfer was used to analyse 3.0 T MRI. Blood samples were analysed for hs-CRP, IL-1RA, IL-6 and TNF-α.

Three subtypes were identified indicating preserved (PIQ), deteriorated (DIQ) and compromised (CIQ) IQ. Absolute total brain volume was significantly smaller in CIQ compared to PIQ and DIQ, and intracranial volume was smaller in CIQ than PIQ (F(2, 124) = 6.407, p = 0.002) indicative of premorbid smaller brain size in the CIQ group. CIQ had higher levels of hs-CRP than PIQ (F(2, 131) = 5.01, p = 0.008). PIQ showed differentially impaired processing speed and verbal learning compared to IQ-matched healthy controls.

The findings add validity of a neurodevelopmental subtype of schizophrenia identified by comparing estimated premorbid and current IQ and characterised by smaller premorbid brain volume and higher measures of low-grade inflammation (CRP).

We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding about the remaining options to achieve the Paris Agreement goals, through overcoming political barriers to carbon pricing, taking into account non-CO2 factors, a well-designed implementation of demand-side and nature-based solutions, resilience building of ecosystems and the recognition that climate change mitigation costs can be justified by benefits to the health of humans and nature alone. We consider new insights about what to expect if we fail to include a new dimension of fire extremes and the prospect of cascading climate tipping elements.

A synthesis is made of 10 topics within climate research, where there have been significant advances since January 2020. The insights are based on input from an international open call with broad disciplinary scope. Findings include: (1) the options to still keep global warming below 1.5 °C; (2) the impact of non-CO2 factors in global warming; (3) a new dimension of fire extremes forced by climate change; (4) the increasing pressure on interconnected climate tipping elements; (5) the dimensions of climate justice; (6) political challenges impeding the effectiveness of carbon pricing; (7) demand-side solutions as vehicles of climate mitigation; (8) the potentials and caveats of nature-based solutions; (9) how building resilience of marine ecosystems is possible; and (10) that the costs of climate change mitigation policies can be more than justified by the benefits to the health of humans and nature.

How do we limit global warming to 1.5 °C and why is it crucial? See highlights of latest climate science.

Psychotic experiences are reported by 5–10% of young people, although only a minority persist and develop into psychotic disorders. It is unclear what characteristics differentiate those with transient psychotic experiences from those with persistent psychotic experiences that are more likely to be of clinical relevance.

To investigate how longitudinal profiles of psychotic experiences, created from assessments at three different time points, are influenced by early life and co-occurring factors.

Using data from 8045 individuals from a birth cohort study, longitudinal profiles of psychotic experiences based on semi-structured interviews conducted at 12, 18 and 24 years were defined. Environmental, cognitive, psychopathological and genetic determinants of these profiles were investigated, along with concurrent changes in psychopathology and cognition.

Following multiple imputations, the distribution of longitudinal profiles of psychotic experiences was none (65.7%), transient (24.1%), low-frequency persistent (8.4%) and high-frequency persistent (1.7%). Individuals with high-frequency persistent psychotic experiences were more likely to report traumatic experiences, other psychopathology, a more externalised locus of control, reduced emotional stability and conscientious personality traits in childhood, compared with those with transient psychotic experiences. These characteristics also differed between those who had any psychotic experiences and those who did not.

These findings indicate that the same risk factors are associated with incidence as with persistence of psychotic experiences. Thus, it might be that the severity of exposure, rather than the presence of specific disease-modifying factors, is most likely to determine whether psychotic experiences are transient or persist, and potentially develop into a clinical disorder over time.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 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.

AAO and PAO are associated with indicators of bipolar disorder 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.

We evaluated the safety and feasibility of high-intensity interval training via a novel telemedicine ergometer (MedBIKE™) in children with Fontan physiology.

The MedBIKE™ is a custom telemedicine ergometer, incorporating a video game platform and live feed of patient video/audio, electrocardiography, pulse oximetry, and power output, for remote medical supervision and modulation of work. There were three study phases: (I) exercise workload comparison between the MedBIKE™ and a standard cardiopulmonary exercise ergometer in 10 healthy adults. (II) In-hospital safety, feasibility, and user experience (via questionnaire) assessment of a MedBIKE™ high-intensity interval training protocol in children with Fontan physiology. (III) Eight-week home-based high-intensity interval trial programme in two participants with Fontan physiology.

There was good agreement in oxygen consumption during graded exercise at matched work rates between the cardiopulmonary exercise ergometer and MedBIKE™ (1.1 ± 0.5 L/minute versus 1.1 ± 0.5 L/minute, p = 0.44). Ten youth with Fontan physiology (11.5 ± 1.8 years old) completed a MedBIKE™ high-intensity interval training session with no adverse events. The participants found the MedBIKE™ to be enjoyable and easy to navigate. In two participants, the 8-week home-based protocol was tolerated well with completion of 23/24 (96%) and 24/24 (100%) of sessions, respectively, and no adverse events across the 47 sessions in total.

The MedBIKE™ resulted in similar physiological responses as compared to a cardiopulmonary exercise test ergometer and the high-intensity interval training protocol was safe, feasible, and enjoyable in youth with Fontan physiology. A randomised-controlled trial of a home-based high-intensity interval training exercise intervention using the MedBIKE™ will next be undertaken.

There is evidence that depression can be prevented; however, traditional approaches face significant scalability issues. Digital technologies provide a potential solution, although this has not been adequately tested. The aim of this study was to evaluate the effectiveness of a new smartphone app designed to reduce depression symptoms and subsequent incident depression amongst a large group of Australian workers.

A randomized controlled trial was conducted with follow-up assessments at 5 weeks and 3 and 12 months post-baseline. Participants were employed Australians reporting no clinically significant depression. The intervention group (N = 1128) was allocated to use HeadGear, a smartphone app which included a 30-day behavioural activation and mindfulness intervention. The attention-control group (N = 1143) used an app which included a 30-day mood monitoring component. The primary outcome was the level of depressive symptomatology (PHQ-9) at 3-month follow-up. Analyses were conducted within an intention-to-treat framework using mixed modelling.

Those assigned to the HeadGear arm had fewer depressive symptoms over the course of the trial compared to those assigned to the control (F3,734.7 = 2.98, p = 0.031). Prevalence of depression over the 12-month period was 8.0% and 3.5% for controls and HeadGear recipients, respectively, with odds of depression caseness amongst the intervention group of 0.43 (p = 0.001, 95% CI 0.26–0.70).

This trial demonstrates that a smartphone app can reduce depression symptoms and potentially prevent incident depression caseness and such interventions may have a role in improving working population mental health. Some caution in interpretation is needed regarding the clinical significance due to small effect size and trial attrition.

Trial Registration Australian and New Zealand Clinical Trials Registry (www.anzctr.org.au/) ACTRN12617000548336

While echocardiographic parameters are used to quantify ventricular function in infants with single ventricle physiology, there are few data comparing these to invasive measurements. This study correlates echocardiographic measures of diastolic function with ventricular end-diastolic pressure in infants with single ventricle physiology prior to superior cavopulmonary anastomosis.

Data from 173 patients enrolled in the Pediatric Heart Network Infant Single Ventricle enalapril trial were analysed. Those with mixed ventricular types (n = 17) and one outlier (end-diastolic pressure = 32 mmHg) were excluded from the analysis, leaving a total sample size of 155 patients. Echocardiographic measurements were correlated to end-diastolic pressure using Spearman’s test.

Median age at echocardiogram was 4.6 (range 2.5–7.4) months. Median ventricular end-diastolic pressure was 7 (range 3–19) mmHg. Median time difference between the echocardiogram and catheterisation was 0 days (range −35 to 59 days). Examining the entire cohort of 155 patients, no echocardiographic diastolic function variable correlated with ventricular end-diastolic pressure. When the analysis was limited to the 86 patients who had similar sedation for both studies, the systolic:diastolic duration ratio had a significant but weak negative correlation with end-diastolic pressure (r = −0.3, p = 0.004). The remaining echocardiographic variables did not correlate with ventricular end-diastolic pressure.

In this cohort of infants with single ventricle physiology prior to superior cavopulmonary anastomosis, most conventional echocardiographic measures of diastolic function did not correlate with ventricular end-diastolic pressure at cardiac catheterisation. These limitations should be factored into the interpretation of quantitative echo data in this patient population.

Offload delay is a prolonged interval between ambulance arrival in the emergency department (ED) and transfer of patient care, typically occurring when EDs are crowded. The offload zone (OZ), which manages ambulance patients waiting for an ED bed, has been implemented to mitigate the impact of ED crowding on ambulance availability. Little is known about the safety or efficiency. The study objectives were to process map the OZ and conduct a hazard analysis to identify steps that could compromise patient safety or process efficiency.

A Health Care Failure Mode and Effect Analysis was conducted. Failure modes (FM) were identified. For each FM, a probability to occur and severity of impact on patient safety and process efficiency was determined, and a hazard score (probability X severity) was calculated. For any hazard score considered high risk, root causes were identified, and mitigations were sought.

The OZ consists of six major processes: 1) patient transported by ambulance, 2) arrival to the ED, 3) transfer of patient care, 4) patient assessment in OZ, 5) patient care in OZ, and 6) patient transfer out of OZ; 78 FM were identified, of which 28 (35.9%) were deemed high risk and classified as impact on patient safety (n=7/28, 25.0%), process efficiency (n=10/28, 35.7%), or both (n=11/28, 39.3%). Seventeen mitigations were suggested.

This process map and hazard analysis is a first step in understanding the safety and efficiency of the OZ. The results from this study will inform current policy and practice, and future work to reduce offload delay.