Autism Spectrum Disorder (ASD) is a complex condition with early childhood onset, characterized by a set of common behavioral features. The etiology of ASD is not yet fully understood; however, it reflects the interaction between genetics and environment. While genetics is now a well-established risk factor, several data support a contribution of the environment as well. This paper summarizes the conclusions of a consensus conference focused on the potential pathogenetic role of environmental factors and on their interactions with genetics. Several environmental factors have been discussed in terms of ASD risk, namely advanced parental age, assisted reproductive technologies, nutritional factors, maternal infections and diseases, environmental chemicals and toxicants, and medications, as well as some other conditions. The analysis focused on their specific impact on three biologically relevant time windows for brain development: the periconception, prenatal, and early postnatal periods. Possible protective factors that might prevent or modify an ASD trajectory have been explored as well. Recommendations for clinicians to reduce ASD risk or its severity have been proposed. Developments in molecular biology and big data approaches, which are able to assess a large number of coexisting factors, are offering new opportunities to disentangle the gene–environment interplay that can lead to the development of ASD.

Gene–environment (GxE) interactions have been related to psychosis spectrum disorders, involving multiple common genetic variants in multiple genes with very small effect sizes, and several environmental factors that constitute a dense network of exposures named the exposome. Here, we aimed to analyze GxE in a cohort of 310 first-episode psychotic (FEP) and 236 healthy controls, by using aggregate scores estimated in large populations such as the polygenic risk score for schizophrenia and (PRS-SCZ) and the Maudsley environmental risk score (ERS). In contrast to previous findings, in our study, the PRS-SCZ did not discriminate cases from controls, but the ERS score explained a similar percentage of the variance as in other studies using similar approaches. Our study supports a positive additive interaction, indicating synergy between genetic susceptibility to schizophrenia (PRS-SCZ dichotomized according to the highest quartile distribution of the control population) and the exposome (ERS > 75% of the controls). This additive interaction showed genetic and environmental dose dependence. Our study shows that the use of aggregate scores derived from large and powered studies instead of statistics derived from specific sample characteristics is a powerful tool for the study of the effects of GxE on the risk of psychotic spectrum disorders. In conclusion, by using a genetic risk score and an ERS we have provided further evidence for the role of GxE in psychosis.

There is great phenotypic heterogeneity within autism spectrum disorders (ASD), which has led to question their classification into a single diagnostic category. The study of the common genetic variation in ASD has suggested a greater contribution of other psychiatric conditions in Asperger syndrome (AS) than in the rest of the DSM-IV ASD subtypes (Non_AS). Here, using available genetic data from previously performed genome-wide association studies (GWAS), we aimed to study the genetic overlap between five of the most related disorders (schizophrenia (SCZ), major depression disorder (MDD), attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorders (OCD) and anxiety (ANX)), and AS, comparing it with the overlap in Non_AS subtypes. A Spanish cohort of autism trios (N = 371) was exome sequenced as part of the Autism Sequencing Consortium (ASC) and 241 trios were extensively characterized to be diagnosed with AS following DSM-IV and Gillberg’s criteria (N = 39) or not (N = 202). Following exome imputation, polygenic risk scores (PRS) were calculated for ASD, SCZ, ADHD, MDD, ANX, and OCD (from available summary data from Psychiatric Genomic Consortium (PGC) repository) in the Spanish trios’ cohort. By using polygenic transmission disequilibrium test (pTDT), we reported that risk for SCZ (P_scz= 0.008, corrected-P_SCZ = 0.0409), ADHD (P_ADHD = 0.021, corrected-P_ADHD = 0.0301), and MDD (P_MDD = 0.039, corrected-P_MDD = 0.0501) is over-transmitted to children with AS but not to Non_AS. Indeed, agnostic clustering procedure with deviation values from pTDT tests suggested two differentiated clusters of subjects, one of which is significantly enriched in AS (P = 0.025). Subsequent analysis with S-Predixcan, a recently developed software to predict gene expression from genotype data, revealed a clear pattern of correlation between cortical gene expression in ADHD and AS (P < 0.001) and a similar strong correlation pattern between MDD and AS, but also extendable to another non-brain tissue such as lung (P < 0.001). Altogether, these results support the idea of AS being qualitatively distinct from Non_AS autism and consistently evidence the genetic overlap between AS and ADHD, MDD, or SCZ.

Background: Clinical intervention in early stages of psychotic disorders is crucial for the prevention of severe symptomatology trajectories and poor outcomes. Genetic variability is studied as a promising modulator of prognosis, thus novel approaches considering the polygenic nature of these complex phenotypes are required to unravel the mechanisms underlying the early progression of the disorder.Methods: The sample comprised of 233 first-episode psychosis (FEP) subjects with clinical and cognitive data assessed periodically for a 2-year period and 150 matched controls. Polygenic risk scores (PRSs) for schizophrenia, bipolar disorder, depression, education attainment and cognitive performance were used to assess the genetic risk of FEP and to characterize their association with premorbid, baseline and progression of clinical and cognitive status.Results: Schizophrenia, bipolar disorder and cognitive performance PRSs were associated with an increased risk of FEP [false discovery rate (FDR) ⩽ 0.027]. In FEP patients, increased cognitive PRSs were found for FEP patients with more cognitive reserve (FDR ⩽ 0.037). PRSs reflecting a genetic liability for improved cognition were associated with a better course of symptoms, functionality and working memory (FDR ⩽ 0.039). Moreover, the PRS of depression was associated with a worse trajectory of the executive function and the general cognitive status (FDR ⩽ 0.001).Conclusions: Our study provides novel evidence of the polygenic bases of psychosis and its clinical manifestation in its first stage. The consistent effect of cognitive PRSs on the early clinical progression suggests that the mechanisms underlying the psychotic episode and its severity could be partially independent.