Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk.

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.

Mapping gray and white matter volume abnormalities in early-onset psychosis: an ENIGMA multicenter voxel-based morphometry study.

INTRODUCTION: Regional gray matter (GM) alterations have been reported in early-onset psychosis (EOP, onset before age 18), but previous studies have yielded conflicting results, likely due to small sample sizes and the different brain regions examined. In this study, we conducted a whole brain voxel-based morphometry (VBM) analysis in a large sample of individuals with EOP, using the newly developed ENIGMA-VBM tool. METHODS: 15 independent cohorts from the ENIGMA-EOP working group participated in the study. The overall sample comprised T1-weighted MRI data from 482 individuals with EOP and 469 healthy controls. Each site performed the VBM analysis locally using the standardized ENIGMA-VBM tool. Statistical parametric T-maps were generated from each cohort and meta-analyzed to reveal voxel-wise differences between EOP and healthy controls as well as the individual-based association between GM volume and age of onset, chlorpromazine (CPZ) equivalent dose, and other clinical variables. RESULTS: Compared with healthy controls, individuals with EOP showed widespread lower GM volume encompassing most of the cortex, with the most marked effect in the left median cingulate (Hedges' g = 0.55, p = 0.001 corrected), as well as small clusters of lower white matter (WM), whereas no regional GM or WM volumes were higher in EOP. Lower GM volume in the cerebellum, thalamus and left inferior parietal gyrus was associated with older age of onset. Deficits in GM in the left inferior frontal gyrus, right insula, right precentral gyrus and right superior frontal gyrus were also associated with higher CPZ equivalent doses. CONCLUSION: EOP is associated with widespread reductions in cortical GM volume, while WM is affected to a smaller extent. GM volume alterations are associated with age of onset and CPZ equivalent dose but these effects are small compared to case-control differences. Mapping anatomical abnormalities in EOP may lead to a better understanding of the role of psychosis in brain development during childhood and adolescence.

Clinical and neurodevelopmental predictors of psychotic disorders in children and adolescents at clinical high risk for psychosis: the CAPRIS study.

BACKGROUND: The neurodevelopmental hypothesis of schizophrenia represents the disorder as an expression of an alteration during the brain development process early in life. Neurodevelopmental variables could become a trait marker, and the study of these variables in children and adolescents at clinical high risk for psychosis (CHR) could identify a specific cluster of patients who later developed psychosis. The aim of this study is to describe clinical and neurodevelopment predictors of transition to psychosis in child and adolescent participants at CHR. Naturalistic longitudinal two-center study of 101 CHR and 110 healthy controls (HC) aged 10-17. CHR participants were children and adolescents aged 10-17, meeting one or more of the CHR criteria assessed at baseline and at 18 months' follow-up. Neurodevelopmental variables assessed were obstetric complications, delay in principal development milestones, and presence of a neurodevelopment diagnosis. Pairwise comparisons, linear regressions, and binary logistic regression were performed.A transition rate of 23.3% at 1.5 years was observed. Participants who developed psychosis (CHR-P) showed higher rates of grandiosity and higher proportions of antipsychotic medication intake at baseline compared to participants who did not develop a psychotic disorder (CHR-NP). In terms of neurodevelopment alterations, CHR-P group showed a higher proportion of participants reporting delay in language development than the CHR-NP and HC groups. The odds of psychosis increased by 6.238 CI 95% [1.276-30.492] for a one-unit increase in having a positive score in grandiosity; they increased by 4.257 95% CI [1.293-14.023] for a one-unit increase in taking antipsychotic medication, and by 4.522 95% [1.185-64.180] for showing language development delay. However, the p-values did not reach significance after adjusting for multiple comparisons.A combination of clinical and neurodevelopmental alterations could help predict the transition to psychotic disorder in a CHR child and adolescent sample. Our results suggest the potential utility of collecting information about neurodevelopment and using these variable multifactorial models to predict psychosis disorders.

Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness.

Over 50% of children with a parent with severe mental illness will develop mental illness by early adulthood. However, intergenerational transmission of risk for mental illness in one's children is insufficiently considered in clinical practice, nor is it sufficiently utilised into diagnostics and care for children of ill parents. This leads to delays in diagnosing young offspring and missed opportunities for protective actions and resilience strengthening. Prior twin, family, and adoption studies suggest that the aetiology of mental illness is governed by a complex interplay of genetic and environmental factors, potentially mediated by changes in epigenetic programming and brain development. However, how these factors ultimately materialise into mental disorders remains unclear. Here, we present the FAMILY consortium, an interdisciplinary, multimodal (e.g., (epi)genetics, neuroimaging, environment, behaviour), multilevel (e.g., individual-level, family-level), and multisite study funded by a European Union Horizon-Staying-Healthy-2021 grant. FAMILY focuses on understanding and prediction of intergenerational transmission of mental illness, using genetically informed causal inference, multimodal normative prediction, and animal modelling. Moreover, FAMILY applies methods from social sciences to map social and ethical consequences of risk prediction to prepare clinical practice for future implementation. FAMILY aims to deliver: (i) new discoveries clarifying the aetiology of mental illness and the process of resilience, thereby providing new targets for prevention and intervention studies; (ii) a risk prediction model within a normative modelling framework to predict who is at risk for developing mental illness; and (iii) insight into social and ethical issues related to risk prediction to inform clinical guidelines.

Mediterranean Diet and Mental Health in Children and Adolescents: A Systematic Review.

CONTEXT: Childhood and adolescence are periods of critical importance in the development of mental health disorders. The Mediterranean diet (MD) has been linked to multiple positive health outcomes, including reduced incidence of mental health disorders and fewer psychiatric symptoms. OBJECTIVE: This study aimed to investigate the association between adherence to an MD and mental health outcomes in children and adolescents. METHODS: A systematic literature review was conducted of original research that explored the relationship between psychiatric symptoms or disorders and adherence to an MD. The literature search was conducted on PubMed, Scopus, Web of Science, MEDES, Dialnet, and Latindex from inception to November 2022, and the Newcastle-Ottawa Scale was used to evaluate the quality of studies. RESULTS: A total of 13 studies (6 cross-sectional, 4 case-control, 2 randomized clinical trials, and 1 longitudinal cohort) out of 450 met the inclusion criteria. A total of 3058 children or adolescents with a mean age range from 8.6 to 16.2 years were included. Among the reviewed studies, 5 (71.42%) of those looking at attention-deficit/hyperactivity disorder, 4 (80%) examining depression, and 2 (50%) assessing anxiety found a significant protective association. Seven articles (53.84%) were found to be of high quality and 6 (46.15%) of moderate quality. CONCLUSION: Adherence to an MD could be a protective factor for mental health in child and adolescent populations. This suggests that promoting an MD could help prevent the onset of clinical psychiatric symptoms, reduce symptom severity, and improve prognosis in young patients. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. CRD42021276316.

Cognitive reserve and cognition in mood disorders: A systematic review and meta-analysis.

Cognitive functioning heterogeneity is a well-recognized phenomenon in individuals diagnosed with mood disorders. Cognitive Reserve (CR) has been linked to multiple positive outcomes, including cognitive performance in these patients. This systematic review and meta-analysis aim to provide a comprehensive analysis of the relationship between CR and cognitive functioning in individuals with mood disorders, including bipolar disorder and depressive disorders. Following PRISMA guidelines, a systematic review and meta-analysis was conducted of original research exploring the relationship between CR and cognitive performance in adult individuals with mood disorders. The literature search was conducted on PubMed, Scopus, and Web of Science, from 2002 to September 2023, and the Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of studies. Overall, 17 studies met the inclusion criteria for the systematic review and 11 for the meta-analysis. Both qualitative and quantitative findings suggested a positive relationship between CR measures and cognitive domains. CR emerges as a possible protective factor for cognitive functioning in adult individuals with mood disorders, potentially helping to mitigate the cognitive impairments associated with the disorder. These findings underscore the importance of the fact that promoting and enhancing CR could help in the cognitive prognosis of this population.

Polygenic risk scores mediating functioning outcomes through cognitive and clinical features in youth at family risk and controls.

Schizophrenia and bipolar disorder exhibit substantial clinical overlap, particularly in individuals at familial high risk, who frequently present sub-threshold symptoms before the onset of illness. Severe mental disorders are highly polygenic traits, but their impact on the stages preceding the manifestation of mental disorders remains relatively unexplored. Our study aimed to examine the influence of polygenic risk scores (PRS) on sub-clinical outcomes over a 2-year period in youth at familial high risk for schizophrenia and bipolar disorder and controls. The sample included 222 children and adolescents, comprising offspring of parents with schizophrenia (n = 38), bipolar disorder (n = 80), and community controls (n = 104). We calculated PRS for psychiatric disorders, neuroticism and cognition using the PRS-CS method. Linear mixed-effects models were employed to investigate the association between PRS and cognition, symptom severity and functioning. Mediation analyses were conducted to explore whether clinical features acted as intermediaries in the impact of PRS on functioning outcomes. SZoff exhibited elevated PRS for schizophrenia. In the entire sample, PRS for depression, neuroticism, and cognitive traits showed associations with sub-clinical features. The effect of PRS for neuroticism and general intelligence on functioning outcomes were mediated by cognition and symptoms severity, respectively. This study delves into the interplay among genetics, the emergence of sub-clinical symptoms and functioning outcomes, providing novel evidence on mechanisms underpinning the continuum from sub-threshold features to the onset of mental disorders. The findings underscore the interplay of genetics, cognition, and clinical features, providing insights for personalized early interventions.