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Stratified medicine holds great promise to tailor treatment to the needs of individual patients. While genetics holds great potential to aid patient stratification, it remains a major challenge to operationalize complex genetic risk factor profiles to deconstruct clinical heterogeneity. Contemporary approaches to this problem rely on polygenic risk scores (PRS), which provide only limited clinical utility and lack a clear biological foundation. To overcome these limitations, we develop the CASTom-iGEx approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue specific gene expression levels. The paradigmatic application of this approach to coronary artery disease or schizophrenia patient cohorts identified diverse strata or biotypes. These biotypes are characterized by distinct endophenotype profiles as well as clinical parameters and are fundamentally distinct from PRS based groupings. In stark contrast to the latter, the CASTom-iGEx strategy discovers biologically meaningful and clinically actionable patient subgroups, where complex genetic liabilities are not randomly distributed across individuals but rather converge onto distinct disease relevant biological processes. These results support the notion of different patient biotypes characterized by partially distinct pathomechanisms. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine paradigms. Stratified medicine promises to tailor treatment for individual patients, however it remains a major challenge to leverage genetic risk data to aid patient stratification. Here the authors introduce an approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue-specific gene expression levels, and highlight its ability to identify biologically meaningful and clinically actionable patient subgroups, supporting the notion of different patient 'biotypes' characterized by partially distinct disease mechanisms. [ABSTRACT FROM AUTHOR]

Stratified medicine holds great promise to tailor treatment to the needs of individual patients. While genetics holds great potential to aid patient stratification, it remains a major challenge to operationalize complex genetic risk factor profiles to deconstruct clinical heterogeneity. Contemporary approaches to this problem rely on polygenic risk scores (PRS), which provide only limited clinical utility and lack a clear biological foundation. To overcome these limitations, we develop the CASTom-iGEx approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue specific gene expression levels. The paradigmatic application of this approach to coronary artery disease or schizophrenia patient cohorts identified diverse strata or biotypes. These biotypes are characterized by distinct endophenotype profiles as well as clinical parameters and are fundamentally distinct from PRS based groupings. In stark contrast to the latter, the CASTom-iGEx strategy discovers biologically meaningful and clinically actionable patient subgroups, where complex genetic liabilities are not randomly distributed across individuals but rather converge onto distinct disease relevant biological processes. These results support the notion of different patient biotypes characterized by partially distinct pathomechanisms. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine paradigms. Stratified medicine promises to tailor treatment for individual patients, however it remains a major challenge to leverage genetic risk data to aid patient stratification. Here the authors introduce an approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue-specific gene expression levels, and highlight its ability to identify biologically meaningful and clinically actionable patient subgroups, supporting the notion of different patient 'biotypes' characterized by partially distinct disease mechanisms. [ABSTRACT FROM AUTHOR]

This study investigated if the association between childhood maltreatment and cognition among psychosis patients and community controls was partially accounted for by genetic liability for psychosis. Patients with first-episode psychosis (N = 755) and unaffected controls (N = 1219) from the EU-GEI study were assessed for childhood maltreatment, intelligence quotient (IQ), family history of psychosis (FH), and polygenic risk score for schizophrenia (SZ-PRS). Controlling for FH and SZ-PRS did not attenuate the association between childhood maltreatment and IQ in cases or controls. Findings suggest that these expressions of genetic liability cannot account for the lower levels of cognition found among adults maltreated in childhood. [ABSTRACT FROM AUTHOR]

Many common illnesses, for reasons that have not been identified, differentially affect men and women. For instance, the autoimmune diseases systemic lupus erythematosus (SLE) and Sjögren's syndrome affect nine times more women than men1, whereas schizophrenia affects men with greater frequency and severity relative to women2. All three illnesses have their strongest common genetic associations in the major histocompatibility complex (MHC) locus, an association that in SLE and Sjögren's syndrome has long been thought to arise from alleles of the human leukocyte antigen (HLA) genes at that locus3–6. Here we show that variation of the complement component 4 (C4) genes C4A and C4B, which are also at the MHC locus and have been linked to increased risk for schizophrenia7, generates 7-fold variation in risk for SLE and 16-fold variation in risk for Sjögren's syndrome among individuals with common C4 genotypes, with C4A protecting more strongly than C4B in both illnesses. The same alleles that increase risk for schizophrenia greatly reduce risk for SLE and Sjögren's syndrome. In all three illnesses, C4 alleles act more strongly in men than in women: common combinations of C4A and C4B generated 14-fold variation in risk for SLE, 31-fold variation in risk for Sjögren's syndrome, and 1.7-fold variation in schizophrenia risk among men (versus 6-fold, 15-fold and 1.26-fold variation in risk among women, respectively). At a protein level, both C4 and its effector C3 were present at higher levels in cerebrospinal fluid and plasma8,9 in men than in women among adults aged between 20 and 50 years, corresponding to the ages of differential disease vulnerability. Sex differences in complement protein levels may help to explain the more potent effects of C4 alleles in men, women's greater risk of SLE and Sjögren's syndrome and men's greater vulnerability to schizophrenia. These results implicate the complement system as a source of sexual dimorphism in vulnerability to diverse illnesses. Sexual dimorphism in genetic vulnerability to schizophrenia, systemic lupus erythematosus and Sjögren's syndrome is linked to differential protein abundance from alleles of complement component 4. [ABSTRACT FROM AUTHOR]

Purpose: The EUropean Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) study contains an unparalleled wealth of comprehensive data that allows for testing hypotheses about (1) variations in incidence within and between countries, including by urbanicity and minority ethnic groups; and (2) the role of multiple environmental and genetic risk factors, and their interactions, in the development of psychotic disorders.Methods: Between 2010 and 2015, we identified 2774 incident cases of psychotic disorders during 12.9 million person-years at risk, across 17 sites in 6 countries (UK, The Netherlands, France, Spain, Italy, and Brazil). Of the 2774 incident cases, 1130 cases were assessed in detail and form the case sample for case-control analyses. Across all sites, 1497 controls were recruited and assessed. We collected data on an extensive range of exposures and outcomes, including demographic, clinical (e.g. premorbid adjustment), social (e.g. childhood and adult adversity, cannabis use, migration, discrimination), cognitive (e.g. IQ, facial affect processing, attributional biases), and biological (DNA via blood sample/cheek swab). We describe the methodology of the study and some descriptive results, including representativeness of the cohort.Conclusions: This resource constitutes the largest and most extensive incidence and case-control study of psychosis ever conducted. [ABSTRACT FROM AUTHOR]

Purpose: To describe pathways to care, duration of untreated psychosis (DUP), and types of interventions provided to first-episode psychosis (FEP) patients by routine Italian mental health services over 5 years since the first service contact.Methods: Naturalistic study conducted in Veneto, within the context of the Psychosis Incident Cohort Outcome Study (PICOS). A comprehensive set of measures was used, including schedules designed to collect information on referrals to psychiatric services and on psychological and pharmacological treatments at 1, 2, and 5 years since first service contact.Results: Overall, 397 patients were assessed. Most engaged with services with the help of family members (47.4%) and through emergency routes (60.3%). Those referred by clinicians were more likely to access care in a non-emergency way. Mean DUP was 5.62 months (SD 11.8) and longer DUP was associated with poorer functioning at 2 and 5 years. Interventions provided over 5 years were mainly constituted by antipsychotic medications (95.4% at 1 year; 85.8% at 2 years; 80.6% at 5 years), whereas a lower percentage (69.1% at 1 year; 61.5% at 2 years; 44.9% at 5 years) also received some forms of psychological interventions, mainly consisting of unspecific support sessions. Other structured interventions, such as CBT or family interventions, were seldom provided at each time-point.Conclusions: Mental health services in Veneto seem effective in engaging FEP patients within a short time since illness onset. However, type of care provided does not meet quality standards recommended by treatment guidelines, especially regarding psychological interventions. [ABSTRACT FROM AUTHOR]

Currently, most of the classification studies of psychosis focused on chronic patients and employed single machine learning approaches. To overcome these limitations, we here compare, to our best knowledge for the first time, different classification methods of first-episode psychosis (FEP) using multi-modal imaging data exploited on several cortical and subcortical structures and white matter fiber bundles. 23 FEP patients and 23 age-, gender-, and race-matched healthy participants were included in the study. An innovative multivariate approach based on multiple kernel learning (MKL) methods was implemented on structural MRI and diffusion tensor imaging. MKL provides the best classification performances in comparison with the more widely used support vector machine, enabling the definition of a reliable automatic decisional system based on the integration of multi-modal imaging information. Our results show a discrimination accuracy greater than 90 % between healthy subjects and patients with FEP. Regions with an accuracy greater than 70 % on different imaging sources and measures were middle and superior frontal gyrus, parahippocampal gyrus, uncinate fascicles, and cingulum. This study shows that multivariate machine learning approaches integrating multi-modal and multisource imaging data can classify FEP patients with high accuracy. Interestingly, specific grey matter structures and white matter bundles reach high classification reliability when using different imaging modalities and indices, potentially outlining a prefronto-limbic network impaired in FEP with particular regard to the right hemisphere. [ABSTRACT FROM AUTHOR]

Neuregulin 1 ( NRG1) and v-erb-a erythroblastic leukemia viral oncogene homolog 4 ( ErbB4) have been extensively studied in schizophrenia susceptibility because of their pivotal role in key neurodevelopmental processes. One of the reasons for the inconsistencies in results could be the fact that the phenotype investigated has mostly the diagnosis of schizophrenia per se, which is widely heterogeneous, both clinically and biologically. In the present study we tested, in a large cohort of 461 schizophrenia patients recruited in Scotland, whether several SNPs in NRG1 and/or ErbB4 are associated with schizophrenia symptom dimensions as evaluated by the Positive and Negative Syndrome Scale (PANSS). We then followed up nominally significant results in a second cohort of 439 schizophrenia subjects recruited in Germany. Using linear regression, we observed two different groups of polymorphisms in NRG1 gene: one showing a nominal association with higher scores of the PANSS positive dimension and the other one with higher scores of the PANSS negative dimension. Regarding ErbB4, a small cluster located in the 5′ end of the gene was detected, showing nominal association mainly with negative, general and total dimensions of the PANSS. These findings suggest that some regions of NRG1 and ErbB4 are functionally involved in biological processes that underlie some of the phenotypic manifestations of schizophrenia. Because of the lack of significant association after correction for multiple testing, our analyses should be considered as exploratory and hypothesis generating for future studies. [ABSTRACT FROM AUTHOR]