Sarah E. Bergen

Both genetic and environmental risk factors contribute to the development of schizophrenia (SCZ) and bipolar disorder (BD), but simultaneous investigation of how these factors influence risk has not yet been comprehensively examined in a large population. Therefore, we aimed to investigate and quantify how a multi-generational index of aggregated genetic risk (family genetic risk scores, FGRS) and environmental exposures jointly contribute to risk for SCZ and BD, and whether these relationships differ between the disorders. We conducted a Swedish register-based matched nested case-control study with 3057 SCZ and 15,029 BD cases diagnosed 1988–2013. We used conditional logistic regression to determine individual and joint effects of established environmental risk factors including adverse childhood experiences (ACEs), substance use, adverse perinatal factors, childhood infections, urban birth and longest residence, and FGRS (quintiles) for SCZ and BD and risk of SCZ/BD. We also estimated population attributable fractions (PAFs) for environmental exposures. FGRS were associated with incremental increases in SCZ and BD, with highest risk observed for the highest quintile (SCZ IRR 9.63, 95% CI 7.17–12.94; BD IRR 6.30, 95% CI 5.80–6.84). FGRS and most environmental exposures were independently associated with risk of SCZ and BD. The greatest PAFs were observed for substance use (SCZ 18.3%; BD 13.2%) and ACEs (SCZ 14.1%; BD 19.8%). FGRS are associated with increased risk for SCZ and BD and were largely independent from environmental risk factors. Potentially modifiable factors, ACEs and substance use, accounted for a moderate proportion of all cases and were particularly impactful for BD (PAF 19.8, 95% CI 18.4, 21.2) and SCZ (PAF 18.3, 95% CI 17.6–19.0), respectively.

Background: The individual effects of genetic factors and adverse childhood experiences (ACEs) on risk of psychosis, including schizophrenia (SCZ) and bipolar disorder (BIP), have been widely acknowledged, but their interaction effects on individual psychopathological symptoms remain unclear. Methods: Based on data from 163,704 individuals in the UK Biobank, we investigated the joint effects of polygenic risk scores (PRSs) of SCZ and BIP and ACEs on psychopathology. ACEs status and 55 psychopathological symptoms from seven domains were measured retrospectively using an online mental health questionnaire in 2016. Recent genome-wide association studies for SCZ and BIP were combined with genotype data to generate PRSs. Logistic regression analyses were then conducted to explore univariate and joint main effects of PRSs and ACEs on psychopathological symptoms, as well as their additive and multiplicative interaction effects. Results: The interaction mechanisms for PRSs and ACEs varied across symptom domains: additive interactions were observed on the depression (RERI _BIP-ACEs = 0.20–0.25), anxiety (RERI _SCZ-ACEs = 0.20; RERI _BIP-ACEs = 0.22–0.26), help-seeking (RERI _SCZ-ACEs = 0.24; RERI _BIP-ACEs = 0.23), and cognition domains (RERI _SCZ-ACEs = −0.23 to -0.17), whereas multiplicative interactions were only detected on the psychotic (beta _SCZ-ACEs = −0.543; beta _BIP-ACEs = −0.181), mania (beta _BIP-ACEs = −0.195), self-harm or suicide (beta _SCZ-ACEs = −0.118), and cognitive domains (beta _SCZ-ACEs = −0.204 to −0.157). Conclusions: The interplay mechanisms for genetic liability to SCZ and BIP and ACEs vary across symptom domains. This study reveals heterogeneity in gene–ACEs interaction mechanisms underlying psychosis and may provide personalized guidance for psychological care after ACEs.

Multidisciplinary evidence support a neurodevelopmental origin for schizophrenia, yet the mechanistic translation of known risk factors remains poorly understood. In this study, we leverage multi-lineage, forebrain-patterned organoids derived from monozygotic twins discordant for schizophrenia, integrating single-cell transcriptomic and epigenomic profiling to uncover disease-associated gene expression and chromatin accessibility topics. By constructing fate probability maps, we identify an accelerated developmental trajectory emerging from a distinct, schizophrenia-associated radial glia cell state, and reveal unique interactions among schizophrenia risk genes through unbiased multimodal analyses. Further, we confirm that schizophrenia-enriched states persist in differentiated lineages and disrupt synaptic programs, accompanied by molecular and cellular phenotypes mimicking observed disease pathology. Collectively, our findings delineate an early disruption in forebrain development, providing novel mechanistic insights into the origins of schizophrenia risk.

Anorexia nervosa (AN) has extensive genetic correlations with other psychiatric disorders, and genetic risk for different psychiatric disorders was associated with distinct clinical courses in AN. Uncovering associations between transdiagnostic psychiatric genetic liability and AN outcomes can facilitate its personalized treatment. In this study, we investigated the associations between transdiagnostic psychiatric genetic liability and outcomes of AN. Genomic structural equation models were fitted to genome-wide association data for AN and psychiatric disorders with high genetic correlations with AN (obsessive-compulsive symptoms [OCS], major depressive disorder [MDD], schizophrenia, and anxiety disorders) to extract one shared and five trait-specific genetic components. Next, we calculated the polygenic risk scores (PRS) for these components, including PRS _shared , PRS _AN-specific , PRS _OCS-specific , PRS _MDD-specific , PRS _SCZ-specific and PRS _ANX-specific , which index the shared genetic liability to all five psychiatric traits, and genetic liability specific to AN, OCS, MDD, SCZ and ANX, respectively. We then tested associations between these PRSs and clinical outcomes reported between 1997 and 2018 among AN cases from the Anorexia Nervosa Genetics Initiative (ANGI), linked to Swedish National Registers. The clinical outcomes included cumulative disease burden (i.e., number of diagnoses, medication prescriptions, and inpatient days), risks of psychiatric comorbidities, and AN symptomatology. Among 4028 included AN cases, the mean (SD) birth year was 1985 (9), and 3947 (98.0%) were female. Within AN, +1 SD increase of PRS _shared was associated with 9–39% excess risk of disease burden and psychiatric comorbidity, whereas the associations between PRS _AN-specific and most clinical outcomes were statistically non-significant. +1 SD increase of PRS _MDD-specific was associated with 3–29% increased risk of AN disease burden. Our findings show that shared psychiatric liability is associated with more adverse AN outcomes, whereas AN-specific liability is not a good indicator for its clinical course. This study provides a novel perspective on factors influencing heterogeneity in AN clinical course.

It is well established that both genetic and environmental factors contribute to risk for schizophrenia (SCZ), and much progress has been made in identifying the specific factors conferring risk. However, the nature and extent of interactions between them has long been a topic of debate. Both the data and methods available to address this have evolved rapidly, enabling new prospects for identifying gene–environment interactions in SCZ. To date, there is limited evidence of strong gene–environment interactions, with environmental factors, molecular genetic risk, and family history simultaneously contributing to risk of SCZ. Still, there are several enduring challenges, some of which can likely be addressed with new tools, methods, and approaches for investigating gene–environment interplay. Consequently, advancements in this field will enhance our capacity to identify individuals most vulnerable to specific environmental exposures, which is pivotal for targeted prevention and intervention.

Schizophrenia (SCZ) and anorexia nervosa (AN) are 2 severe and highly heterogeneous disorders showing substantial familial co-aggregation. Genetic factors play a significant role in both disorders, but the shared genetic etiology between them is yet to be investigated. Using summary statistics from recent large genome-wide association studies on SCZ (N_cases = 53 386) and AN (N_cases = 16 992), a 2-sample Mendelian randomization analysis was conducted to explore the causal relationship between SCZ and AN. MiXeR was employed to quantify their polygenic overlap. A conditional/conjunctional false discovery rate (condFDR/conjFDR) framework was adopted to identify loci jointly associated with both disorders. Functional annotation and enrichment analyses were performed on the shared loci. We observed a cross-trait genetic enrichment, a suggestive bidirectional causal relationship, and a considerable polygenic overlap (Dice coefficient = 62.2%) between SCZ and AN. The proportion of variants with concordant effect directions among all shared variants was 69.9%. Leveraging overlapping genetic associations, we identified 6 novel loci for AN and 33 novel loci for SCZ at condFDR <0.01. At conjFDR <0.05, we identified 10 loci jointly associated with both disorders, implicating multiple genes highly expressed in the cerebellum and pituitary and involved in synapse organization. Particularly, high expression of the shared genes was observed in the hippocampus in adolescence and orbitofrontal cortex during infancy. This study provides novel insights into the relationship between SCZ and AN by revealing a shared genetic component and offers a window into their complex etiology.

Background: Shared genetic risk between schizophrenia (SCZ) and bipolar disorder (BD) is well-established, yet the extent to which they share environmental risk factors remains unclear. We compare the associations between environmental exposures during childhood/prior to disorder onset with the risk of developing SCZ and BD.Methods: We conducted a Swedish register-based nested case–control study using 4184 SCZ cases and 18 681 BD cases diagnosed 1988–2013. Cases were matched to five controls by birth year, birth region, and sex. Conditional logistic regression was used to estimate incidence rate ratios (IRR) for SCZ and BD for each exposure (severe childhood infections, adverse childhood experiences (ACEs), substance use disorders (SUDs), urban birth/longest residence).Results: All SUD types were associated with very high risk (IRR 4.9–25.5), and all forms of ACEs with higher risk (IRR 1.5–4.3) for both disorders. In the mutually adjusted models, ACEs demonstrated slightly higher risk for BD (SCZ IRR 1.30, 1.19-1.42; BD IRR 1.49, 1.44–1.55), while for SUD, risk was higher for SCZ (SCZ IRR 9.43, 8.15–10.92; BD IRR 5.50, 5.15–5.88). Infections were associated with increased risk of BD (IRR 1.21, 1.17–1.26) but not SCZ. Urban birth and urban longest residence were associated with higher risk of SCZ (IRR 1.19, 1.03–1.37), while only the combination of urban birth and rural longest residence showed higher risk for BD (IRR 1.24, 1.13–1.35).Conclusions: There were both shared and unique environmental risk factors: SUDs and ACEs were risk factors for both disorders, while infections were more strongly associated with BD and urbanicity with SCZ.