Patients can respond differently to intervention in the early phase of psychosis. Diverse symptomatic and functional outcomes can be distinguished and achieving one outcome may mean achieving another, but not necessarily the other way round, which is difficult to disentangle with cross-sectional data. The present study's goal was to evaluate implicative relationships between diverse functional outcomes to better understand their reciprocal dependencies in a cross-sectional design, by using statistical implication analysis (SIA).

Early psychosis patients of an early intervention program were evaluated for different outcomes (symptomatic response, functional recovery, and working/living independently) after 36 months of treatment. To determine which positive outcomes implied other positive outcomes, SIA was conducted by using the Iota statistical implication index, a newly developed approach allowing to measure asymmetrical bidirectional relationships between outcomes.

Two hundred and nineteen recent onset patients with early psychosis were assessed. Results at the end of the three-years in TIPP showed that working independently statistically implied achieving all other outcomes. Symptomatic and functional recovery reciprocally implied one another. Living independently weakly implied symptomatic and functional recovery and did not imply independent working.

The concept of implication is an interesting way of evaluating dependencies between outcomes as it allows us to overcome the tendency to presume symmetrical relationships between them. We argue that a better understanding of reciprocal dependencies within psychopathology can provide an impetus to tailormade treatments and SIA is a useful tool to address this issue in cross-sectional designs.

There is a lack of standardised psychometric data in electronic health record (EHR)-based research. Proxy measures of symptom severity based on patients' clinical records may be useful surrogates in mental health EHR research.

This study aimed to validate proxy tools for the short versions of the Positive and Negative Syndrome Scale (PANSS-6), Young Mania Rating Scale (YMRS-6) and Montgomery–Åsberg Depression Rating Scale (MADRS-6).

A cross-sectional, multicentre study was conducted in a sample of 116 patients with first-episode psychosis from 12 public hospitals in Spain. Concordance between PANSS-6, YMRS-6 and MADRS-6 scores and their respective proxies was evaluated based on information from EHR clinical notes, using a variety of statistical procedures, including multivariate tests to adjust for potential confounders. Bootstrapping techniques were used for internal validation, and an independent cohort from the Treatment and Early Intervention in Psychosis Program (TIPP-Lausanne, Switzerland) for external validation.

The proxy versions correlated strongly with their respective standardised scales (partial correlations ranged from 0.75 to 0.84) and had good accuracy and discriminatory power in distinguishing between patients in and not in remission (percentage of patients correctly classified ranged from 83.9 to 91.4% and bootstrapped optimism-corrected area under the receiver operating characteristic curve ranged from 0.76 to 0.89), with high interrater reliability (intraclass correlation coefficient of 0.81). The findings remained robust in the external validation data-set.

The proxy instruments proposed for assessing psychotic and affective symptoms by reviewing EHR provide a feasible and reliable alternative to traditional structured psychometric procedures, and a promising methodology for real-world practice settings.

Frequently associated with early psychosis, depressive and manic dimensions may play an important role in its course and outcome. While manic and depressive symptoms can alternate and co-occur, most of the studies in early intervention investigated these symptoms independently. The aim of this study was therefore to explore the co-occurrence of manic and depressive dimensions, their evolution and impact on outcomes.

We prospectively studied first-episode psychosis patients (N = 313) within an early intervention program over 3 years. Based on latent transition analysis, we identified sub-groups of patients with different mood profiles considering both manic and depressive dimensions, and studied their outcomes.

Our results revealed six different mood profiles at program entry and after 1.5 years follow-up (absence of mood disturbance, co-occurrence, mild depressive, severe depressive, manic and hypomanic), and four after 3 years (absence of mood disturbance, co-occurrence, mild depressive and hypomanic). Patients with absence of mood disturbance at discharge had better outcomes. All patients with co-occurring symptoms at program entry remained symptomatic at discharge. Patients with mild depressive symptoms were less likely to return to premorbid functional level at discharge than the other subgroups. Patients displaying a depressive component had poorer quality of physical and psychological health at discharge.

Our results confirm the major role played by mood dimensions in early psychosis, and show that profiles with co-occurring manic and depressive dimensions are at risk of poorer outcome. An accurate assessment and treatment of these dimensions in people with early psychosis is crucial.

Early-onset psychosis (EOP) refers to the development of a first episode of psychosis before 18 years of age. Individuals at clinical high risk for psychosis (CHR-P) include adolescents and young adults, although most evidence has focused on adults. Negative symptoms are important prognostic indicators in psychosis. However, research focusing on children and adolescents is limited.

To provide meta-analytical evidence and a comprehensive review of the status and advances in the diagnosis, prognosis and treatment of negative symptoms in children and adolescents with EOP and at CHR-P.

PRISMA/MOOSE-compliant systematic review (PROSPERO: CRD42022360925) from inception to 18 August 2022, in any language, to identify individual studies conducted in EOP/CHR-P children and adolescents (mean age <18 years) providing findings on negative symptoms. Findings were systematically appraised. Random-effects meta-analyses were performed on the prevalence of negative symptoms, carrying out sensitivity analyses, heterogeneity analyses, publication bias assessment and quality assessment using the Newcastle–Ottawa Scale.

Of 3289 articles, 133 were included (n = 6776 EOP, mean age 15.3 years (s.d. = 1.6), males = 56.1%; n = 2138 CHR-P, mean age 16.1 years (s.d. = 1.0), males = 48.6%). There were negative symptoms in 60.8% (95% CI 46.4%–75.2%) of the children and adolescents with EOP and 79.6% (95% CI 66.3–92.9%) of those at CHR-P. Prevalence and severity of negative symptoms were associated with poor clinical, functional and intervention outcomes in both groups. Different interventions were piloted, with variable results requiring further replication.

Negative symptoms are common in children and adolescents at early stages of psychosis, particularly in those at CHR-P, and are associated with poor outcomes. Future intervention research is required so that evidence-based treatments will become available.

Childhood adversity and cannabis use are considered independent risk factors for psychosis, but whether different patterns of cannabis use may be acting as mediator between adversity and psychotic disorders has not yet been explored. The aim of this study is to examine whether cannabis use mediates the relationship between childhood adversity and psychosis.

Data were utilised on 881 first-episode psychosis patients and 1231 controls from the European network of national schizophrenia networks studying Gene–Environment Interactions (EU-GEI) study. Detailed history of cannabis use was collected with the Cannabis Experience Questionnaire. The Childhood Experience of Care and Abuse Questionnaire was used to assess exposure to household discord, sexual, physical or emotional abuse and bullying in two periods: early (0–11 years), and late (12–17 years). A path decomposition method was used to analyse whether the association between childhood adversity and psychosis was mediated by (1) lifetime cannabis use, (2) cannabis potency and (3) frequency of use.

The association between household discord and psychosis was partially mediated by lifetime use of cannabis (indirect effect coef. 0.078, s.e. 0.022, 17%), its potency (indirect effect coef. 0.059, s.e. 0.018, 14%) and by frequency (indirect effect coef. 0.117, s.e. 0.038, 29%). Similar findings were obtained when analyses were restricted to early exposure to household discord.

Harmful patterns of cannabis use mediated the association between specific childhood adversities, like household discord, with later psychosis. Children exposed to particularly challenging environments in their household could benefit from psychosocial interventions aimed at preventing cannabis misuse.

While cannabis use is a well-established risk factor for psychosis, little is known about any association between reasons for first using cannabis (RFUC) and later patterns of use and risk of psychosis.

We used data from 11 sites of the multicentre European Gene-Environment Interaction (EU-GEI) case–control study. 558 first-episode psychosis patients (FEPp) and 567 population controls who had used cannabis and reported their RFUC.

We ran logistic regressions to examine whether RFUC were associated with first-episode psychosis (FEP) case–control status. Path analysis then examined the relationship between RFUC, subsequent patterns of cannabis use, and case–control status.

Controls (86.1%) and FEPp (75.63%) were most likely to report ‘because of friends’ as their most common RFUC. However, 20.1% of FEPp compared to 5.8% of controls reported: ‘to feel better’ as their RFUC (χ2 = 50.97; p < 0.001). RFUC ‘to feel better’ was associated with being a FEPp (OR 1.74; 95% CI 1.03–2.95) while RFUC ‘with friends’ was associated with being a control (OR 0.56; 95% CI 0.37–0.83). The path model indicated an association between RFUC ‘to feel better’ with heavy cannabis use and with FEPp-control status.

Both FEPp and controls usually started using cannabis with their friends, but more patients than controls had begun to use ‘to feel better’. People who reported their reason for first using cannabis to ‘feel better’ were more likely to progress to heavy use and develop a psychotic disorder than those reporting ‘because of friends’.

Prevention of violent behaviors (VB) in the early phase of psychosis (EPP) is a real challenge. Impulsivity was shown to be strongly related to VB, and different evolutions of impulsivity were noticed along treatments. One possible variable involved in the relationship between VB and the evolution of impulsivity is cannabis use (CU). The high prevalence of CU in EPP and its relationship with VB led us to investigate: 1/the impact of CU and 2/the impact of early CU on the evolution of impulsivity levels during a 3-year program, in violent and non-violent EPP patients.

178 non-violent and 62 violent patients (VPs) were followed-up over a 3 year period. Age of onset of CU was assessed at program entry and impulsivity was assessed seven times during the program. The evolution of impulsivity level during the program, as a function of the violent and non-violent groups of patients and CU precocity were analyzed with linear mixed-effects models.

Over the treatment period, impulsivity level did not evolve as a function of the interaction between group and CU (coef. = 0.02, p = 0.425). However, when including precocity of CU, impulsivity was shown to increase significantly only in VPs who start consuming before 15 years of age (coef. = 0.06, p = 0.008).

The precocity of CU in VPs seems to be a key variable of the negative evolution of impulsivity during follow-up and should be closely monitored in EPP patients entering care since they have a higher risk of showing VB.

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.

A history of childhood adversity is associated with psychotic disorder, with an increase in risk according to the number of exposures. However, it is not known why only some exposed individuals go on to develop psychosis. One possibility is pre-existing polygenic vulnerability. Here, we investigated, in the largest sample of first-episode psychosis (FEP) cases to date, whether childhood adversity and high polygenic risk scores for schizophrenia (SZ-PRS) combine synergistically to increase the risk of psychosis, over and above the effect of each alone.

We assigned a schizophrenia-polygenic risk score (SZ-PRS), calculated from the Psychiatric Genomics Consortium (PGC2), to all participants in a sample of 384 FEP patients and 690 controls from the case–control component of the EU-GEI study. Only participants of European ancestry were included in the study. A history of childhood adversity was collected using the Childhood Trauma Questionnaire (CTQ). Synergistic effects were estimated using the interaction contrast ratio (ICR) [odds ratio (OR)exposure and PRS − ORexposure − ORPRS + 1] with adjustment for potential confounders.

There was some evidence that the combined effect of childhood adversities and polygenic risk was greater than the sum of each alone, as indicated by an ICR greater than zero [i.e. ICR 1.28, 95% confidence interval (CI) −1.29 to 3.85]. Examining subtypes of childhood adversities, the strongest synergetic effect was observed for physical abuse (ICR 6.25, 95% CI −6.25 to 20.88).

Our findings suggest possible synergistic effects of genetic liability and childhood adversity experiences in the onset of FEP, but larger samples are needed to increase precision of estimates.

It is unclear what the prevalence of metabolic syndrome (MetS) in drug-naïve first-episode of psychosis (FEP) is, as previous meta-analyses were conducted in minimally exposed or drug-naïve FEP patients with psychotic disorder at any stage of the disease; thus, a meta-analysis examining MetS in naïve FEP compared with the general population is needed.

Studies on individuals with FEP defined as drug-naïve (0 days exposure to antipsychotics) were included to conduct a systematic review. A meta-analysis of proportions for the prevalence of MetS in antipsychotic-naïve patients was performed. Prevalence estimates and 95% CI were calculated using a random-effect model. Subgroup analyses and meta-regressions to identify sources and the amount of heterogeneity were also conducted.

The search yielded 4143 articles. After the removal of duplicates, 2473 abstracts and titles were screened. At the full-text stage, 112 were screened, 18 articles were included in a systematic review and 13 articles in the main statistical analysis. The prevalence of MetS in naïve (0 days) FEP is 13.2% (95% CI 8.7–19.0). Ethnicity accounted for 3% of the heterogeneity between studies, and diagnostic criteria used for MetS accounted for 7%. When compared with controls matched by sex and age, the odds ratio is 2.52 (95% CI 1.29–5.07; p = 0.007).

Our findings of increased rates of MetS in naïve FEP patients suggest that we are underestimating cardiovascular risk in this population, especially in those of non-Caucasian origin. Our findings support that altered metabolic parameters in FEPs are not exclusively due to antipsychotic treatments.

Although evidence from psychosis patients demonstrates the adverse effects of cannabis use (CU) at a young age and that the rate of CU is high in subgroups of young violent patients with psychotic disorders, little is known about the possible effect of the age of onset of CU on later violent behaviors (VB). So, we aimed to explore the impact of age at onset of CU on the risk of displaying VB in a cohort of early psychosis patients.

Data were collected prospectively over a 36-month period in the context of an early psychosis cohort study. A total of 265 patients, aged 18–35 years, were included in the study. Logistic regression was performed to assess the link between age of onset of substance use and VB.

Among the 265 patients, 72 had displayed VB and 193 had not. While violent patients began using cannabis on average at age 15.29 (0.45), nonviolent patients had started on average at age 16.97 (0.35) (p = 0.004). Early-onset CU (up to age 15) was a risk factor for VB (odds ratio = 4.47, confidence interval [CI]: 1.13–20.06) when the model was adjusted for age group, other types of substance use, being a user or a nonuser and various violence risk factors and covariates. History of violence and early CU (until 15) were the two main risk factors for VB.

Our results suggest that early-onset CU may play a role in the emergence of VB in early psychosis.