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Schizophrenia (SZ), bipolar disorder (BD) and depression (D) run in families. This susceptibility is partly due to hundreds or thousands of common genetic variants, each conferring a fractional risk. The cumulative effects of the associated variants can be summarised as a polygenic risk score (PRS). Using data from the EUropean Network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) first episode case–control study, we aimed to test whether PRSs for three major psychiatric disorders (SZ, BD, D) and for intelligent quotient (IQ) as a neurodevelopmental proxy, can discriminate affective psychosis (AP) from schizophrenia-spectrum disorder (SSD).
Participants (842 cases, 1284 controls) from 16 European EU-GEI sites were successfully genotyped following standard quality control procedures. The sample was stratified based on genomic ancestry and analyses were done only on the subsample representing the European population (573 cases, 1005 controls). Using PRS for SZ, BD, D, and IQ built from the latest available summary statistics, we performed simple or multinomial logistic regression models adjusted for 10 principal components for the different clinical comparisons.
In case–control comparisons PRS-SZ, PRS-BD and PRS-D distributed differentially across psychotic subcategories. In case–case comparisons, both PRS-SZ [odds ratio (OR) = 0.7, 95% confidence interval (CI) 0.54–0.92] and PRS-D (OR = 1.31, 95% CI 1.06–1.61) differentiated AP from SSD; and within AP categories, only PRS-SZ differentiated BD from psychotic depression (OR = 2.14, 95% CI 1.23–3.74).
Combining PRS for severe psychiatric disorders in prediction models for psychosis phenotypes can increase discriminative ability and improve our understanding of these phenotypes. Our results point towards the potential usefulness of PRSs in specific populations such as high-risk or early psychosis phases.
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.
In March 2020 SPFT was preparing for the first wave of the COVID-19 pandemic. Senior medical leadership supported the rapid development and delivery of SBE workshop for assessment and management of physically unwell patients in a psychiatric setting in the context of COVID-19. The training was delivered to 102 psychiatrists across 10 sessions over 4 weeks.
A learning review was completed to identify lessons learned from the delivery of this SBE workshop.
The intervention was reviewed using open-space feedback from attendees, interviews with facilitators and medical leadership, and SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis.
Overall, the simulation project met its pre-determined objectives of increasing confidence and competence in the medical workforce in the context of COVID-19 and physical health. Development and delivery of the workshop was rapid, with request to delivery taking 4 days.
A summary of the key lessons include:
An existing simulation faculty within the trust was essential, allowing for rapid identification of key stakeholders and those able to deliver the project.
A “direct-line” relationship to senior leadership enabled the project to be dynamic and responsive to changing demands as COVID-19 guidelines and objectives evolved.
Redeploying higher trainees with SBE experience to develop the project as a focussed team allowed for rapid delivery which was resource-effective.
The workforce found reassurance from understanding what was not expected of them, as much as what was. For example, making clear that Arterial Blood Gases would not be introduced to the psychiatric setting.
There is an ongoing learning need for physical health training through SBE in non-covid scenarios.
SBE can be an effective intervention for a range of medical grades and covering a large geographical area.
There are opportunities for developing multi-disciplinary training on physical health in psychiatry.
We have outlined some of the key learning outcomes from a successfully implemented SBE project during the first COVID-19 wave in spring 2020. The project has cemented the role of the relatively new simulation faculty within the trust and highlighted the effectiveness of close collaboration between leadership and a small, dedicated group of facilitators. The project has continued to be used for training new staff members and the resources have been widely shared, used by other NHS trusts and also internationally.
At the start of the COVID-19 pandemic there was significant uncertainty for the NHS and it's workforce. Within psychiatry, there was an expectation that junior doctors would be redeployed, with senior psychiatrists stepping down to cover physical health and on-call duties.
Senior leadership in mental health trusts were also preparing for COVID-19 outbreaks on psychiatric wards and were developing strategies for managing a novel illness with a poorly understood clinical course. Many psychiatrist expressed anxieties around their competency in assessing and managing acutely physically unwell patients in a mental health setting.
This project aimed to improve confidence of psychiatrists in core physical health competencies through devising and delivering an evolving SBE package.
Sussex Partnership Foundation Trust redeployed two higher trainees from their simulation faculty to work full time on developing a SBE package. This was requested by senior leadership to deliver training about assessing and managing physically unwell patients in the context of COVID-19. This training was devised as a 90 minute didactic lecture following by 90 minutes of SBE.
This was delivered at 6 sites through 10 opt-in sessions available to all doctors in the trust over 4 weeks. Pre and post-course questionnaires were given to all participants to measure the effect.
102 medical staff attended the SBE workshops. Feedback was completed by 93 (91%) doctors prior to the course and 97 (95%) post. Before the workshop, 33% did not feel they had a structured approach for assessing an acutely unwell patient, which reduced to 0% after completing the course.
On a 5-point Likert scale, confidence in managing COVID-19 symptoms increased from 2.54/5 to 4.07/5 overall with 89% of doctors feeling “confident” or “very confident”. There were similar increases in confidence in managing critically unwell patients (2.7/5 pre; 3.95/5 post) and in identifying alternative causes for acutely unwell patients (2.63/5 pre; 4.02/5 post).
This project demonstrates that SBE is an effective way to rapidly develop effective interventions for the medical workforce, increasing confidence in the face of significant uncertainty and reducing anxiety within the system to meet the learning needs identified by medical leadership.
As part of this project Sussex Partnership Medical Education freely shared the workshop materials, which were later adopted and used by psychiatry departments internationally.
Helminth infections in wood mice (n = 483), trapped over a period of 26 years in the woods surrounding Malham Tarn in North Yorkshire, were analysed. Although 10 species of helminths were identified, the overall mean species richness was 1.01 species/mouse indicating that the helminth community was relatively depauperate in this wood mouse population. The dominant species was Heligmosomoides polygyrus, the prevalence (64.6%) and abundance (10.4 worms/mouse) of which declined significantly over the study period. Because of the dominance of this species, analyses of higher taxa (combined helminths and combined nematodes) also revealed significantly declining values for prevalence, although not abundance. Helminth species richness (HSR) and Brillouin's index of diversity (BID) did not show covariance with year, neither did those remaining species whose overall prevalence exceeded 5% (Syphacia stroma, Aonchotheca murissylvatici and Plagiorchis muris). Significant age effects were detected for the prevalence and abundance of all higher taxa, H. polygyrus and P. muris, and for HSR and BID, reflecting the accumulation of helminths with increasing host age. Only two cases of sex bias were found; male bias in abundance of P. muris and combined Digenea. We discuss the significance of these results and hypothesize about the underlying causes.
The growth in wirelessly enabled sensor network technologies has enabled the low cost deployment of sensor platforms with applications in a range of sectors and communities. In the agricultural domain such sensors have been the foundation for the creation of decision support tools that enhance farm operational efficiency. This Research Reflection illustrates how these advances are assisting dairy farmers to optimise performance and illustrates where emerging sensor technology can offer additional benefits. One of the early applications for sensor technology at an individual animal level was the accurate identification of cattle entering into heat (oestrus) to increase the rate of successful pregnancies and thus optimise milk yield per animal. This was achieved through the use of activity monitoring collars and leg tags. Additional information relating to the behaviour of the cattle, namely the time spent eating and ruminating, was subsequently derived from collars giving further insights of economic value into the wellbeing of the animal, thus an enhanced range of welfare related services have been provisioned. The integration of the information from neck-mounted collars with the compositional analysis data of milk measured at a robotic milking station facilitates the early diagnosis of specific illnesses such as mastitis. The combination of different data streams also serves to eliminate the generation of false alarms, improving the decision making capability. The principle of integrating more data streams from deployed on-farm systems, for example, with feed composition data measured at the point of delivery using instrumented feeding wagons, supports the optimisation of feeding strategies and identification of the most productive animals. Optimised feeding strategies reduce operational costs and minimise waste whilst ensuring high welfare standards. These IoT-inspired solutions, made possible through Internet-enabled cloud data exchange, have the potential to make a major impact within farming practices. This paper gives illustrative examples and considers where new sensor technology from the automotive industry may also have a role.
Brain imaging studies have shown altered amygdala activity during emotion processing in children and adolescents with oppositional defiant disorder (ODD) and conduct disorder (CD) compared to typically developing children and adolescents (TD). Here we aimed to assess whether aggression-related subtypes (reactive and proactive aggression) and callous-unemotional (CU) traits predicted variation in amygdala activity and skin conductance (SC) response during emotion processing.
We included 177 participants (n = 108 cases with disruptive behaviour and/or ODD/CD and n = 69 TD), aged 8–18 years, across nine sites in Europe, as part of the EU Aggressotype and MATRICS projects. All participants performed an emotional face-matching functional magnetic resonance imaging task.
Differences between cases and TD in affective processing, as well as specificity of activation patterns for aggression subtypes and CU traits, were assessed. Simultaneous SC recordings were acquired in a subsample (n = 63). Cases compared to TDs showed higher amygdala activity in response to negative faces (fearful and angry) v. shapes. Subtyping cases according to aggression-related subtypes did not significantly influence on amygdala activity; while stratification based on CU traits was more sensitive and revealed decreased amygdala activity in the high CU group. SC responses were significantly lower in cases and negatively correlated with CU traits, reactive and proactive aggression.
Our results showed differences in amygdala activity and SC responses to emotional faces between cases with ODD/CD and TD, while CU traits moderate both central (amygdala) and peripheral (SC) responses. Our insights regarding subtypes and trait-specific aggression could be used for improved diagnostics and personalized treatment.
Previous studies have reported that the menopause is associated with deterioration in memory and mood in some women. Also, a significant body of research suggests that hormone ‘replacement’ therapy (HRT) – now referred to as menopausal hormone therapy (MHT) – specifically with estrogen, may act as a prophylaxis against the risk for developing Alzheimer’s disease (AD) and a treatment for perimenopausal depression. The precise nature, and biological basis, of this relationship is still not fully understood. However, it probably involves a complex interaction between genes, the environment and the mode and timing of MHT prescription. Increasing our understanding of the interplay between these factors during the menopause may permit us to target more specific treatments to vulnerable individuals. Furthermore, it offers a window of opportunity to understand the putative role of estrogen in psychiatric disorders at other times of the reproductive cycle. The current chapter will focus on the role of estrogen on Alzheimer’s disease and depression during the menopause.
Optical Photothermal Infrared (O-PTIR) spectroscopy is a new technique for measuring submicron spatial resolution IR spectra with little or no sample preparation. This speeds up analysis times benefiting high-volume manufacturers through gaining insight into process contamination that occurs during development and on production lines. The ability to rapidly obtain far-field non-contact IR spectra at high spatial resolution facilitates the chemical identification of small organic contaminants that are not possible to measure with conventional Fourier transform infrared (FT-IR) microspectroscopy. The unique pump-probe system architecture also facilitates submicron simultaneous IR + Raman microscopy from the same spot with the same spatial resolution. With these unique capabilities, O-PTIR is finding utilization in the high-volume and high-value industries of high-tech componentry (memory storage, electronics, displays, etc.).
First episode psychosis (FEP) patients who use cannabis experience more frequent psychotic and euphoric intoxication experiences compared to controls. It is not clear whether this is consequent to patients being more vulnerable to the effects of cannabis use or to their heavier pattern of use. We aimed to determine whether extent of use predicted psychotic-like and euphoric intoxication experiences in patients and controls and whether this differs between groups.
We analysed data on patients who had ever used cannabis (n = 655) and controls who had ever used cannabis (n = 654) across 15 sites from six countries in the EU-GEI study (2010–2015). We used multiple regression to model predictors of cannabis-induced experiences and to determine if there was an interaction between caseness and extent of use.
Caseness, frequency of cannabis use and money spent on cannabis predicted psychotic-like and euphoric experiences (p ⩽ 0.001). For psychotic-like experiences (PEs) there was a significant interaction for caseness × frequency of use (p < 0.001) and caseness × money spent on cannabis (p = 0.001) such that FEP patients had increased experiences at increased levels of use compared to controls. There was no significant interaction for euphoric experiences (p > 0.5).
FEP patients are particularly sensitive to increased psychotic-like, but not euphoric experiences, at higher levels of cannabis use compared to controls. This suggests a specific psychotomimetic response in FEP patients related to heavy cannabis use. Clinicians should enquire regarding cannabis related PEs and advise that lower levels of cannabis use are associated with less frequent PEs.
The ‘jumping to conclusions’ (JTC) bias is associated with both psychosis and general cognition but their relationship is unclear. In this study, we set out to clarify the relationship between the JTC bias, IQ, psychosis and polygenic liability to schizophrenia and IQ.
A total of 817 first episode psychosis patients and 1294 population-based controls completed assessments of general intelligence (IQ), and JTC, and provided blood or saliva samples from which we extracted DNA and computed polygenic risk scores for IQ and schizophrenia.
The estimated proportion of the total effect of case/control differences on JTC mediated by IQ was 79%. Schizophrenia polygenic risk score was non-significantly associated with a higher number of beads drawn (B = 0.47, 95% CI −0.21 to 1.16, p = 0.17); whereas IQ PRS (B = 0.51, 95% CI 0.25–0.76, p < 0.001) significantly predicted the number of beads drawn, and was thus associated with reduced JTC bias. The JTC was more strongly associated with the higher level of psychotic-like experiences (PLEs) in controls, including after controlling for IQ (B = −1.7, 95% CI −2.8 to −0.5, p = 0.006), but did not relate to delusions in patients.
Our findings suggest that the JTC reasoning bias in psychosis might not be a specific cognitive deficit but rather a manifestation or consequence, of general cognitive impairment. Whereas, in the general population, the JTC bias is related to PLEs, independent of IQ. The work has the potential to inform interventions targeting cognitive biases in early psychosis.
We describe an ultra-wide-bandwidth, low-frequency receiver recently installed on the Parkes radio telescope. The receiver system provides continuous frequency coverage from 704 to 4032 MHz. For much of the band (
), the system temperature is approximately 22 K and the receiver system remains in a linear regime even in the presence of strong mobile phone transmissions. We discuss the scientific and technical aspects of the new receiver, including its astronomical objectives, as well as the feed, receiver, digitiser, and signal processor design. We describe the pipeline routines that form the archive-ready data products and how those data files can be accessed from the archives. The system performance is quantified, including the system noise and linearity, beam shape, antenna efficiency, polarisation calibration, and timing stability.
Daily use of high-potency cannabis has been reported to carry a high risk for developing a psychotic disorder. However, the evidence is mixed on whether any pattern of cannabis use is associated with a particular symptomatology in first-episode psychosis (FEP) patients.
We analysed data from 901 FEP patients and 1235 controls recruited across six countries, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) study. We used item response modelling to estimate two bifactor models, which included general and specific dimensions of psychotic symptoms in patients and psychotic experiences in controls. The associations between these dimensions and cannabis use were evaluated using linear mixed-effects models analyses.
In patients, there was a linear relationship between the positive symptom dimension and the extent of lifetime exposure to cannabis, with daily users of high-potency cannabis having the highest score (B = 0.35; 95% CI 0.14–0.56). Moreover, negative symptoms were more common among patients who never used cannabis compared with those with any pattern of use (B = −0.22; 95% CI −0.37 to −0.07). In controls, psychotic experiences were associated with current use of cannabis but not with the extent of lifetime use. Neither patients nor controls presented differences in depressive dimension related to cannabis use.
Our findings provide the first large-scale evidence that FEP patients with a history of daily use of high-potency cannabis present with more positive and less negative symptoms, compared with those who never used cannabis or used low-potency types.
Posttraumatic stress disorder (PTSD) is often complicated by the after-effects of mild traumatic brain injury (mTBI). The mixture of brain conditions results in abnormal affective and cognitive functioning, as well as maladaptive behavior. To better understand how brain activity explains cognitive and emotional processes in these conditions, we used an emotional N-back task and functional magnetic resonance imaging (fMRI) to study neural responses in US military veterans after deployments to Iraq and Afghanistan. Additionally, we sought to examine whether hierarchical dimensional models of maladaptive personality could account for the relationship between combat-related brain conditions and fMRI responses under cognitive and affective challenge. FMRI data, measures of PTSD symptomatology (PTSS), blast-induced mTBI (bmTBI) severity, and maladaptive personality (MMPI-2-RF) were gathered from 93 veterans. Brain regions central to emotion regulation were selected for analysis, and consisted of bilateral amygdala, bilateral dorsolateral prefrontal (dlPFC), and ventromedial prefrontal/subgenual anterior cingulate (vmPFC-sgACC). Cognitive load increased activity in dlPFC and reduced activity in emotional responding brain regions. However, individuals with greater PTSS showed blunted deactivations in bilateral amygdala and vmPFC-sgACC, and weaker responses in right dlPFC. Additionally, we found that elevated emotional/internalizing dysfunction (EID), specifically low positive emotionality (RC2), accounted for PTSS-related changes in bilateral amygdala under increased cognitive load. Findings suggest that PTSS might result in amygdala and vmPFC-sgACC activity resistant to moderation by cognitive demands, reflecting emotion dysregulation despite a need to marshal cognitive resources. Anhedonia may be an important target for interventions that improve the affective and cognitive functioning of individuals with PTSD.