Negative symptoms predict adverse outcomes within psychotic disorders, in individuals at high-risk for psychosis, and in young people in the community. There is considerable interest in the dimensional structure of negative symptoms in clinical samples, and accumulating evidence suggests a 5-factor structure. Little is known about the underlying structure of negative symptoms in young people despite the importance of this developmental stage for mental health. We used confirmatory factor analysis to test the structure of parent-reported negative symptoms at mean ages 16.32 (SD 0.68, N = 4974), 17.06 (SD 0.88, N = 1469) and 22.30 (SD 0.93, N = 5179) in a community sample. Given previously reported associations between total negative symptoms and genome-wide polygenic scores (GPS) for major depressive disorder (MDD) and schizophrenia in adolescence, we assessed associations between individual subdomains and these GPSs. A 5-factor model of flat affect, alogia, avolition, anhedonia and asociality provided the best fit at each age and was invariant over time. The results of our linear regression analyses showed associations between MDD GPS with avolition, flat affect, anhedonia and asociality, and between schizophrenia GPS with avolition and flat affect. We showed that a 5-factor structure of negative symptoms is present from ages 16 to 22 in the community. Avolition was most consistently associated with polygenic liability to MDD and schizophrenia, and alogia was least associated. These findings highlight the value of dissecting negative symptoms into psychometrically derived subdomains and may offer insights into early manifestation of genetic risk for MDD and schizophrenia.

Background Psychotic experiences (PEs) such as paranoia and hallucinations, and negative symptoms (NS) such as anhedonia and flat affect are common in adolescence. Psychotic experiences and negative symptoms (PENS) increase risk for later psychiatric outcomes, particularly when they persist. The extent to which genetic and environmental influences contribute to the stability of PENS in mid‐to‐late adolescence is unknown. Methods Using the Specific Psychotic Experiences Questionnaire (SPEQ) twice across ~9 months in adolescence, N = 1,448 twin pairs [M = 16.32 (0.68)] reported experiences of paranoia, hallucinations, cognitive disorganization, grandiosity and anhedonia, and their parents reported on a range of NS. Individuals were split into low‐scoring, decreasing, increasing and persistent groups for each subscale. Frequencies and mean differences in distress, depression traits and emotional problems were investigated across groups. Longitudinal structural equation modelling was used to estimate the aetiological components underlying the stability of PENS. Results Phenotypic stability was moderate for all PENS (r = .59–.69). Persistent PENS across 9 months were associated with greater levels of distress (V = 0.15–0.46, for PEs only), depression traits (d = 0.47–1.67, except grandiosity) and emotional problems (d = 0.47–1.47, except grandiosity and anhedonia) at baseline compared to groups with transitory or low levels of PENS. At both ages PENS were heritable and influenced by shared and nonshared environment. Genetic influences contributed 38%–62% and shared environment contributed 13%–33% to the stability of PENS. Nonshared environment contributed 34%–41% (12% for parent‐rated NS). There was strong overlap of genetic and shared environmental influences across time, and lower overlap for nonshared environment. Imperfect stability of PENS was at least partly due to nonshared environmental influences. Conclusions When adolescent PENS persist over time, they are often characterized by more distress, and higher levels of other psychopathology. Both genetic and environmental effects influence stability of PENS.

Background Psychotic experiences and negative symptoms (PENS) are common in non-clinical populations. PENS are associated with adverse outcomes, particularly when they persist. Little is known about the trajectories of PENS dimensions in young people, nor about the precursory factors associated with these trajectories. Methods We conducted growth mixture modelling of paranoia, hallucinations, and negative symptoms across ages 16, 17, and 22 in a community sample (N = 12 049–12 652). We then described the emergent trajectory classes through their associations with genome-wide polygenic scores (GPS) for psychiatric and educational phenotypes, and earlier childhood characteristics. Results Three trajectory classes emerged for paranoia, two for hallucinations, and two for negative symptoms. Across PENS, GPS for clinical help-seeking, major depressive disorder, and attention deficit hyperactivity disorder were associated with increased odds of being in the most elevated trajectory class (OR 1.07–1.23). Lower education GPS was associated with the most elevated trajectory class for hallucinations and negative symptoms (OR 0.77–0.91). Conversely for paranoia, higher education GPS was associated with the most elevated trajectory class (OR 1.25). Trajectory class associations were not significant for schizophrenia, obsessive-compulsive disorder, bipolar disorder, or anorexia GPS. Emotional/behaviour problems and life events in childhood were associated with increased odds of being in the most elevated trajectory class across PENS. Conclusions Our results suggest latent heterogeneity in the development of paranoia, hallucinations, and negative symptoms in young people that is associated with specific polygenic scores and childhood characteristics.

We conducted growth mixture modelling of paranoia, hallucinations, and negative symptoms across ages 16, 17, and 22 in a community sample (N = 12,049-12,652). We then described the emergent trajectory classes through their associations with polygenic scores for psychiatric and educational phenotypes, and earlier childhood characteristics. Our results suggest systematic heterogeneity in the development of paranoia, hallucinations, and negative symptoms in young people that is associated with specific polygenic scores and childhood characteristics.

Background: Youth adversity (e.g., abuse and bullying victimisation) is robust risk factor for later mental health problems (e.g., depression and anxiety). Research shows the prevalence of youth adversity and rates of mental health problems vary by individual characteristics, identity or social groups (e.g., gender and ethnicity). However, little is known about whether the impact of youth adversity on mental health problems differ across the intersections of these characteristics (e.g., white female). This paper reports on a component of the ATTUNE research programme (work package 2) which aims to investigate the impact and mechanisms of youth adversity on depressive and anxiety symptoms in young people by intersectionality profiles. Methods: The data are from 4 UK adolescent cohorts: HeadStart Cornwall, Oxwell, REACH, and DASH. These cohorts were assembled for adolescents living in distinct geographical locations representing coastal, suburban and urban places in the UK. Youth adversity was assessed using a series of self-report questionnaires and official records. Validated self-report instruments measured depressive and anxiety symptoms.  A range of different variables were classified as possible social and cognitive mechanisms. Results and analysis: Structural equation modelling (e.g., multiple group models, latent growth models) and multilevel modelling will be used, with adaptation of methods to suit the specific available data, in accord with statistical and epidemiological conventions. Discussion: The results from this research programme will broaden our understanding of the association between youth adversity and mental health, including new information about intersectionality and related mechanisms in young people in the UK. The findings will inform future research, clinical guidance, and policy to protect and promote the mental health of those most vulnerable to the negative consequences of youth adversity.