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Studies investigating cognitive impairments in psychosis and depression have typically compared the average performance of the clinical group against healthy controls (HC), and do not report on the actual prevalence of cognitive impairments or strengths within these clinical groups. This information is essential so that clinical services can provide adequate resources to supporting cognitive functioning. Thus, we investigated this prevalence in individuals in the early course of psychosis or depression.
A comprehensive cognitive test battery comprising 12 tests was completed by 1286 individuals aged 15–41 (mean age 25.07, s.d. 5.88) from the PRONIA study at baseline: HC (N = 454), clinical high risk for psychosis (CHR; N = 270), recent-onset depression (ROD; N = 267), and recent-onset psychosis (ROP; N = 295). Z-scores were calculated to estimate the prevalence of moderate or severe deficits or strengths (>2 s.d. or 1–2 s.d. below or above HC, respectively) for each cognitive test.
Impairment in at least two cognitive tests was as follows: ROP (88.3% moderately, 45.1% severely impaired), CHR (71.2% moderately, 22.4% severely impaired), ROD (61.6% moderately, 16.2% severely impaired). Across clinical groups, impairments were most prevalent in tests of working memory, processing speed, and verbal learning. Above average performance (>1 s.d.) in at least two tests was present for 40.5% ROD, 36.1% CHR, 16.1% ROP, and was >2 SDs in 1.8% ROD, 1.4% CHR, and 0% ROP.
These findings suggest that interventions should be tailored to the individual, with working memory, processing speed, and verbal learning likely to be important transdiagnostic targets.
Little is still known about the long-term impact of childhood and adolescent persistent depression and anxiety in adulthood.
To investigate the impact of persistent anxiety, depression, and comorbid anxiety and depression across childhood and adolescence on the development of multiple adverse outcomes in young adulthood.
This study used data from 8122 participants in the Avon Longitudinal Study of Parents and Children cohort. The Development and Well-Being Assessment (DAWBA) examined child anxiety and depression symptomatology. The DAWBA generalised anxiety and mood subscales at 8, 10 and 13 years were selected, and a measure of comorbid anxiety and depression symptoms was created at each time point. Further, several mental and physical health, substance misuse and education/employment problems were assessed at 24 years. Latent class growth analyses were used to detect trajectories of anxiety, depression and comorbid anxiety and depression; and logistic regression to examine how persistent anxiety, depression or both were associated with adverse outcomes at 24 years.
All three classes with persistent anxiety, depression or both were significantly associated with presenting with any mental health problems and any education/employment problem. Persistent high levels of depression and high levels of comorbid anxiety and depression, but not persistent high anxiety, were significantly associated with any physical health problem. High levels of comorbid anxiety and depression was the only DAWBA domain significantly associated with substance misuse; and overall, this was the domain that exerted the greatest negative impact, as it presented the highest odd ratio values.
Children and adolescents with comorbid anxiety and depression are at the highest risk for having more adverse outcomes at 24 years.
There is ongoing debate on the nosological position of bipolar disorder (BD) and borderline personality disorder (BPD). Identifying the unique and shared risks, developmental pathways, and symptoms in emerging BD and BPD could help the field refine aetiological hypotheses and improve the prediction of the onset of these disorders. This study aimed to: (a) systematically synthesise the available evidence from systematic reviews (SRs) and meta-analyses (MAs) concerning environmental, psychosocial, biological, and clinical factors leading to the emergence of BD and BPD; (b) identify the main differences and common features between the two disorders to characterise their complex interplay and, (c) highlight remaining evidence gaps.
Data sources were; PubMed, PsychINFO, Embase, Cochrane, CINAHL, Medline, ISI Web of Science. Overlap of included SRs/MAs was assessed using the corrected covered area process. The methodological quality of each included SR and MA was assessed using the AMSTAR.
22 SRs and MAs involving 249 prospective studies met eligibility criteria. Results demonstrated that family history of psychopathology, affective instability, attention deficit hyperactivity disorder, anxiety disorders, depression, sleep disturbances, substance abuse, psychotic symptoms, suicidality, childhood adversity and temperament were common predisposing factors across both disorders. There are also distinct factors specific to emerging BD or BPD.
Prospective studies are required to increase our understanding of the development of BD and BPD onset and their complex interplay by concurrently examining multiple measures in BD and BPD at-risk populations.
There is still an ongoing debate on the nosological position of Bipolar Disorder (BD) and Borderline Personality Disorder (BPD). Identifying the unique and shared risks and developmental pathways in emerging BD and BPD could help the field refine aetiological hypotheses of these disorders. The study aims were to systematically synthesise the available evidence from systematic reviews and meta-analyses concerning environmental, psychosocial, biological, and clinical factors leading to the emergence of BD and BPD to identify the main differences and common characteristics between the two disorders to characterise their complex interplay whilst highlighting remaining evidence gaps.
A literature search was conducted PubMed, PsychINFO, EMBASE, Cochrane, CINAHL, MEDLINE, and ISI Web of Science as the data sources. 19 systematic reviews and meta-analyses involving 217 prospective studies met eligibility criteria.
Results demonstrated that family history of psychopathology, affective instability, attention deficit hyperactivity disorder, anxiety disorders, depression, sleep disturbances, substance abuse, psychotic symptoms, suicidality, childhood adversity and temperament dimensions were common predisposing factors across both disorders. There are also many distinct variables that could be found early in the course of both disorders. Most of the factors should be considered as a general, nonspecific precursor signs and symptoms of both BPD and BD, apart from subsyndromal depression, subsyndromal hypomania, cyclothymia disorder, psychotic symptoms, age at onset of major depression and frequency and loading of affective symptoms.
Although the findings of this review may lead to support the view of BD and BPD as two distinct disorders, there is not sufficient data to either indicate that BD and BPD are separate nosological entities or that BPD should be considered as an extension of BD disorders. Future research is required to increase our understanding of the aetiology of BD and BPD onset and their complex interplay by conducting prospective studies which concurrently examine multiple measures including biological, environmental, psychosocial and clinical factors in BD and BPD at-risk populations. Large, multilevel data sets will enable deep phenotyping and distinguish pathophysiological pathways.
Progress in developing personalised care for mental disorders is supported by numerous proof-of-concept machine learning studies in the area of risk assessment, diagnostics and precision prescribing. Most of these studies primarily use clinical data, but models might benefit from additional neuroimaging, blood and genetic data to improve accuracy. Combined, multimodal models might offer potential for stratification of patients for treatment. Clinical implementation of machine learning is impeded by a lack of wider generalisability, with efforts primarily focused on psychosis and dementia. Studies across all diagnostic groups should work to test the robustness of machine learning models, which is an essential first step to clinical implementation, and then move to prospective clinical validation. Models need to exceed clinicians’ heuristics to be useful, and safe, in routine decision-making. Engagement of clinicians, researchers and patients in digitalisation and ‘big data’ approaches are vital to allow the generation and accessibility of large, longitudinal, prospective data needed for precision psychiatry to be applied into real-world psychiatric care.
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).
Clinical high-risk states for psychosis (CHR) are associated with functional impairments and depressive disorders. A previous PRONIA study predicted social functioning in CHR and recent-onset depression (ROD) based on structural magnetic resonance imaging (sMRI) and clinical data. However, the combination of these domains did not lead to accurate role functioning prediction, calling for the investigation of additional risk dimensions. Role functioning may be more strongly associated with environmental adverse events than social functioning.
We aimed to predict role functioning in CHR, ROD and transdiagnostically, by adding environmental adverse events-related variables to clinical and sMRI data domains within the PRONIA sample.
Baseline clinical, environmental and sMRI data collected in 92 CHR and 95 ROD samples were trained to predict lower versus higher follow-up role functioning, using support vector classification and mixed k-fold/leave-site-out cross-validation. We built separate predictions for each domain, created multimodal predictions and validated them in independent cohorts (74 CHR, 66 ROD).
Models combining clinical and environmental data predicted role outcome in discovery and replication samples of CHR (balanced accuracies: 65.4% and 67.7%, respectively), ROD (balanced accuracies: 58.9% and 62.5%, respectively), and transdiagnostically (balanced accuracies: 62.4% and 68.2%, respectively). The most reliable environmental features for role outcome prediction were adult environmental adjustment, childhood trauma in CHR and childhood environmental adjustment in ROD.
Findings support the hypothesis that environmental variables inform role outcome prediction, highlight the existence of both transdiagnostic and syndrome-specific predictive environmental adverse events, and emphasise the importance of implementing real-world models by measuring multiple risk dimensions.
Personalised prediction of functional outcomes is a promising approach for targeted early intervention in psychiatry. However, generalisability and resource efficiency of such prognostic models represent challenges. In the PRONIA study (German Clinical Trials Register: DRKS00005042), we demonstrate excellent generalisability of prognostic models in individuals at clinical high-risk for psychosis or with recent-onset depression, and substantial contributions of detailed clinical phenotyping, particularly to the prediction of role functioning. These results indicate that it is possible that functioning prediction models based only on clinical data could be effectively applied in diverse healthcare settings, so that neuroimaging data may not be needed at early assessment stages.
There is consistent evidence that psychosis is associated with a degree of peripheral immune activation. Many studies and meta-analyses report increased circulating concentrations of pro-inflammatory cytokines including IL-6, IL-1β and TNF-α together with acute phase proteins, such as CRP in patients with psychosis compared with controls. Meta-analysis confirms increased circulating IL-6 and other inflammatory markers in medication-naïve first-episode psychosis (FEP) (1), and in the CSF of schizophrenia patients compared with controls (2). Longitudinal studies show an association between elevated IL-6/CRP in childhood/adolescence and risk of psychotic symptoms or diagnosis of schizophrenia in adulthood (3,4). Genetic analysis shows that possession of a functional variant in the IL-6 R gene (Asp358Ala, rs2228145), which is known to reduce the activity of IL-6, is also associated with decreased risk of psychosis (5). This suggests that the association of raised IL-6 with psychosis may be causal and not due to reverse causality or residual confounding, i.e., the effect of a factor associated with psychosis that also by chance increases levels of this cytokine. However, Mendelian randomization analysis also suggests that elevated CRP levels may be protective for schizophrenia (6), in contrast to observational studies consistently reporting higher CRP levels in patients with the illness compared with controls (7). Divergent results for two known pro-inflammatory markers raises questions about potential mechanisms though which immune dysfunction may influence brain and behaviour to increase the risk of psychotic disorders. One explanation is that genetically predicted levels of low CRP may predispose to infections, which in turn, may increase schizophrenia risk through immune and non-immune mechanisms (6,8).
Psychosis expression in the general population may reflect a behavioral manifestation of the risk for psychotic disorder. It can be conceptualized as an interconnected system of psychotic and affective experiences; a so-called ‘symptom network’. Differences in demographics, as well as exposure to adversities and risk factors, may produce substantial heterogeneity in symptom networks, highlighting potential etiological divergence in psychosis risk.
To explore this idea in a data-driven way, we employed a novel recursive partitioning approach in the 2007 English National Survey of Psychiatric Morbidity (N = 7242). We sought to identify ‘network phenotypes’ by explaining heterogeneity in symptom networks through potential moderators, including age, sex, ethnicity, deprivation, childhood abuse, separation from parents, bullying, domestic violence, cannabis use, and alcohol.
Sex was the primary source of heterogeneity in symptom networks. Additional heterogeneity was explained by interpersonal trauma (childhood abuse and domestic violence) in women and domestic violence, cannabis use, ethnicity in men. Among women, especially those exposed to early interpersonal trauma, an affective loading within psychosis may have distinct relevance. Men, particularly those from minority ethnic groups, demonstrated a strong network connection between hallucinatory experiences and persecutory ideation.
Symptom networks of psychosis expression in the general population are highly heterogeneous. The structure of symptom networks seems to reflect distinct sex-related adversities, etiologies, and mechanisms of symptom-expression. Disentangling the complex interplay of sex, minority ethnic group status, and other risk factors may help optimize early intervention and prevention strategies in psychosis.
Childhood trauma (CT) is associated with an increased risk of mental health disorders; however, it is unknown whether this represents a diagnosis-specific risk factor for specific psychopathology mediated by structural brain changes. Our aim was to explore whether (i) a predictive CT pattern for transdiagnostic psychopathology exists, and whether (ii) CT can differentiate between distinct diagnosis-dependent psychopathology. Furthermore, we aimed to identify the association between CT, psychopathology and brain structure.
We used multivariate pattern analysis in data from 643 participants of the Personalised Prognostic Tools for Early Psychosis Management study (PRONIA), including healthy controls (HC), recent onset psychosis (ROP), recent onset depression (ROD), and patients clinically at high-risk for psychosis (CHR). Participants completed structured interviews and self-report measures including the Childhood Trauma Questionnaire, SCID diagnostic interview, BDI-II, PANSS, Schizophrenia Proneness Instrument, Structured Interview for Prodromal Symptoms and structural MRI, analyzed by voxel-based morphometry.
(i) Patients and HC could be distinguished by their CT pattern with a reasonable precision [balanced accuracy of 71.2% (sensitivity = 72.1%, specificity = 70.4%, p ≤ 0.001]. (ii) Subdomains ‘emotional neglect’ and ‘emotional abuse’ were most predictive for CHR and ROP, while in ROD ‘physical abuse’ and ‘sexual abuse’ were most important. The CT pattern was significantly associated with the severity of depressive symptoms in ROD, ROP, and CHR, as well as with the PANSS total and negative domain scores in the CHR patients. No associations between group-separating CT patterns and brain structure were found.
These results indicate that CT poses a transdiagnostic risk factor for mental health disorders, possibly related to depressive symptoms. While differences in the quality of CT exposure exist, diagnostic differentiation was not possible suggesting a multi-factorial pathogenesis.
Auditory Verbal Hallucinations (AVH) are a hallmark of psychosis, but affect many other clinical populations. Patients’ understanding and self-management of AVH may differ between diagnostic groups, change over time, and influence clinical outcomes.
We aimed to explore patients’ understanding and self-management of AVH in a young adult clinical population.
35 participants reporting frequent AVH were purposively sampled from a youth mental health service, to capture experiences across psychosis and non-psychosis diagnoses. Diary and photo-elicitation methodologies were used – participants were asked to complete diaries documenting experiences of AVH, and to take photographs representing these experiences. In-depth, unstructured interviews were held, using participant-produced materials as a topic guide. Conventional content analysis was conducted, deriving results from the data in the form of themes.
Three themes emerged:
(1) Searching for answers, forming identities – voice-hearers sought to explain their experiences, resulting in the construction of identities for voices, and descriptions of relationships with them. These identities were drawn from participants’ life-stories (e.g., reflecting trauma), and belief-systems (e.g., reflecting supernatural beliefs, or mental illness). Some described this process as active / volitional. Participants described re-defining their own identities in relation to those constructed for AVH (e.g. as diseased, 'chosen', or persecuted), others considered AVH explicitly as aspects of, or changes in, their personality.
(2) Coping strategies and goals – patients’ self-management strategies were diverse, reflecting the diverse negative experiences of AVH. Strategies were related to a smaller number of goals, e.g. distraction, soothing overwhelming emotions, 'reality-checking', and retaining agency.
(3) Outlook – participants formed an overall outlook reflecting their self-efficacy in managing AVH. Resignation and hopelessness in connection with disabling AVH are contrasted with outlooks of “acceptance” or integration, which were described as positive, ideal, or mature.
Trans-diagnostic commonalities in understanding and self-management of AVH are highlighted - answer-seeking and identity-formation processes; a diversity of coping strategies and goals; and striving to accept the symptom. Descriptions of “voices-as-self”, and dysfunctional relationships with AVH, could represent specific features of voice-hearing in personality disorder, whereas certain supernatural/paranormal identities and explanations were clearly delusional. However, no aspect of identity-formation was completely unique to psychosis or non-psychosis diagnostic groups. The identity-formation process, coping strategies, and outlooks can be seen as a framework both for individual therapies and further research.
Psychosis is a major mental illness with first onset in young adults. The prognosis is poor in around half of the people affected, and difficult to predict. The few tools available to predict prognosis have major weaknesses which limit their use in clinical practice. We aimed to develop and validate a risk prediction model of symptom non-remission in first-episode psychosis.
Our development cohort consisted of 1027 patients with first-episode psychosis recruited between 2005 to 2010 from 14 early intervention services across the National Health Service in England. Our validation cohort consisted of 399 patients with first-episode psychosis recruited between 2006 to 2009 from a further 11 English early intervention services. The one-year non-remission rate was 52% and 54% in the development and validation cohorts, respectively. Multivariable logistic regression was used to develop a risk prediction model for non-remission, which was externally validated.
The prediction model showed good discrimination (C-statistic of 0.74 (0.72, 0.76) and adequate calibration with intercept alpha of 0.13 (0.03, 0.23) and slope beta of 0.99 (0.87, 1.12). Our model improved the net-benefit by 16% at a risk threshold of 50%, equivalent to 16 more detected non-remitted first-episode psychosis individuals per 100 without incorrectly classifying remitted cases.
Once prospectively validated, our first episode psychosis prediction model could help identify patients at increased risk of non-remission at initial clinical contact.
Depression in first-episode psychosis (FEP) is highly prevalent and associated with poor outcomes; it has become increasingly recognised and adopted in national and international guidelines for psychosis. Using a 26-item questionnaire, this study aimed to explore if this shift has led to greater recognition among UK psychiatrists, and more effective management of depression in FEP.
Of the 297 respondents, 54.4% observed depression occurring in chronic psychosis, with the least number of respondents (17.7%) identifying depression occurring frequently during FEP. Although there was reasonable agreement in the use of antidepressants as a first-line treatment for depression (70% prescribing antidepressants), there was uncertainty around assessing depression and delineating from psychosis symptoms, and particularly negative symptoms.
Evidence-based treatments for comorbid depression in psychosis will lead to clearer national guidelines, allowing for optimal management of depression in early psychosis, potentially leading to improved outcomes for these individuals.
Women in academic publishing and academic psychiatry face many challenges of gender inequality, including significant pay differentials, poor visibility in senior positions and a male-dominated hierarchical system. We discuss this problem and outline how the BJPsych plans to tackle these issues it in its own publishing.
Treatment resistance causes significant burden in psychosis. Clozapine is the only evidence-based pharmacologic intervention available for people with treatment-resistant schizophrenia; current guidelines recommend commencement after two unsuccessful trials of standard antipsychotics.
This paper aims to explore the prevalence of treatment resistance and pathways to commencement of clozapine in UK early intervention in psychosis (EIP) services.
Data were taken from the National Evaluation of the Development and Impact of Early Intervention Services study (N = 1027) and included demographics, medication history and psychosis symptoms measured by the Positive and Negative Syndrome Scale (PANSS) at baseline, 6 months and 12 months. Prescribing patterns and pathways to clozapine were examined. We adopted a strict criterion for treatment resistance, defined as persistent elevated positive symptoms (a PANSS positive score ≥16, equating to at least two items of at least moderate severity), across three time points.
A total of 143 (18.1%) participants met the definition of treatment resistance of having continuous positive symptoms over 12 months, despite treatment in EIP services. Sixty-one (7.7%) participants were treatment resistant and eligible for clozapine, having had two trials of standard antipsychotics; however, only 25 (2.4%) were prescribed clozapine over the 12-month study period. Treatment-resistant participants were more likely to be prescribed additional antipsychotic medication and polypharmacy, instead of clozapine.
Prevalent treatment resistance was observed in UK EIP services, but prescription of polypharmacy was much more common than clozapine. Significant delays in the commencement of clozapine may reflect a missed opportunity to promote recovery in this critical period.
There is increasing interest in the clinical and aetiological overlap between autism spectrum disorders and schizophrenia spectrum disorders, reported to co-occur at both diagnostic and trait levels. Individually, sub-clinical autistic and psychotic traits are associated with poor clinical outcomes, including increased depressive symptomatology, self-harming behaviour and suicidality. However, the implications when both traits co-occur remain poorly understood. The study aimed to (1) examine the relationship between autistic and psychotic traits and (2) determine if their co-occurrence increases depressive symptomatology, self-harm and suicidality.
Cross-sectional data from a self-selecting (online and poster advertising) sample of the adult UK population (n = 653) were collected using an online survey. Validated self-report measures were used to assess sub-clinical autistic and psychotic traits, depressive symptomatology, self-harming behaviour and suicidality. Correlation and regression analyses were performed.
A positive correlation between sub-clinical autistic and positive psychotic traits was confirmed (rs = 0.509, p < 0.001). Overall, autistic traits and psychotic traits were, independently, significant predictors of depression, self-harm and suicidality. Intriguingly, however, depression was associated with a negative interaction between the autistic domain attention to detail and psychotic traits.
This study supports previous findings that sub-clinical autistic and psychotic traits are largely independently associated with depression, self-harm and suicidality, and is novel in finding that their combined presence has no additional effect on depression, self-harm or suicidality. These findings highlight the importance of considering both autistic and psychotic traits and their symptom domains in research and when developing population-based depression prevention and intervention strategies.
A reliable biomarker signature for bipolar disorder sensitive to illness phase would be of considerable clinical benefit. Among circulating blood-derived markers there has been a significant amount of research into inflammatory markers, neurotrophins and oxidative stress markers.
To synthesise and interpret existing evidence of inflammatory markers, neurotrophins and oxidative stress markers in bipolar disorder focusing on the mood phase of illness.
Following PRISMA (Preferred Reporting Items for Systematic reviews and Meta-analyses) guidelines, a systematic review was conducted for studies investigating peripheral biomarkers in bipolar disorder compared with healthy controls. We searched Medline, Embase, PsycINFO, SciELO and Web of Science, and separated studies by bipolar mood phase (mania, depression and euthymia). Extracted data on each biomarker in separate mood phases were synthesised using random-effects model meta-analyses.
In total, 53 studies were included, comprising 2467 cases and 2360 controls. Fourteen biomarkers were identified from meta-analyses of three or more studies. No biomarker differentiated mood phase in bipolar disorder individually. Biomarker meta-analyses suggest a combination of high-sensitivity C-reactive protein/interleukin-6, brain derived neurotrophic factor/tumour necrosis factor (TNF)-α and soluble TNF-α receptor 1 can differentiate specific mood phase in bipolar disorder. Several other biomarkers of interest were identified.
Combining biomarker results could differentiate individuals with bipolar disorder from healthy controls and indicate a specific mood-phase signature. Future research should seek to test these combinations of biomarkers in longitudinal studies.