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Abstract Autism spectrum disorder (ASD) is a highly heritable condition with a large variation in cognitive function. Here we investigated the shared genetic architecture between cognitive traits (intelligence (INT) and educational attainment (EDU)), and risk loci jointly associated with ASD and the cognitive traits. We analyzed data from genome-wide association studies (GWAS) of INT (n = 269,867), EDU (n = 766,345) and ASD (cases n = 18,381, controls n = 27,969). We used the bivariate causal mixture model (MiXeR) to estimate the total number of shared genetic variants, local analysis of co-variant annotation (LAVA) to estimate local genetic correlations, conditional false discovery rate (cond/conjFDR) to identify specific overlapping loci. The MiXeR analyses showed that 12.7k genetic variants are associated with ASD, of which 12.0k variants are shared with EDU, and 11.1k are shared with INT with both positive and negative relationships within overlapping variants. The majority (59–68%) of estimated shared loci have concordant effect directions, with a positive, albeit modest, genetic correlation between ASD and EDU (rg = 0.21, p = 2e−13) and INT (rg = 0.22, p = 4e−12). We discovered 43 loci jointly associated with ASD and cognitive traits (conjFDR

Abstract Anorexia nervosa (AN) is a heritable eating disorder (50–60%) with an array of commonly comorbid psychiatric disorders and related traits. Although significant genetic correlations between AN and psychiatric disorders and related traits have been reported, their shared genetic architecture is largely understudied. We investigated the shared genetic architecture of AN and schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), mood instability (Mood), neuroticism (NEUR), and intelligence (INT). We applied the conditional false discovery rate (FDR) method to identify novel risk loci for AN, and conjunctional FDR to identify loci shared between AN and related phenotypes, to summarize statistics from relevant genome-wide association studies (GWAS). Individual GWAS samples varied from 72,517 to 420,879 participants. Using conditional FDR we identified 58 novel AN loci. Furthermore, we identified 38 unique loci shared between AN and major psychiatric disorders (SCZ, BIP, and MD) and 45 between AN and psychological traits (Mood, NEUR, and INT). In line with genetic correlations, the majority of shared loci showed concordant effect directions. Functional analyses revealed that the shared loci are involved in 65 unique pathways, several of which overlapped across analyses, including the “signal by MST1” pathway involved in Hippo signaling. In conclusion, we demonstrated genetic overlap between AN and major psychiatric disorders and related traits, and identified novel risk loci for AN by leveraging this overlap. Our results indicate that some shared characteristics between AN and related disorders and traits may have genetic underpinnings.

Abstract Both environmental (e.g. interpersonal traumatization during childhood and adolescence) and genetic factors may contribute to the development of Borderline Personality Disorder (BPD). Twin studies assessing borderline personality symptoms/features in the general population indicate that genetic factors underlying these symptoms/features are shared in part with the personality traits of the Five Factor Model (FFM) of personality—the “Big Five”. In the present study, the genetic overlap of BPD with the Big Five -Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism- was assessed. Linkage disequilibrium score regression was used to calculate genetic correlations between a genome-wide association study (GWAS) in central European populations on BPD (N = 2543) and GWAS on the Big Five (N = 76,551–122,886, Neuroticism N = 390,278). Polygenic scores (PGS) were calculated to test the association of the genetic disposition for the personality traits with BPD case-control status. Significant positive genetic correlations of BPD were found with Neuroticism (rg = 0.34, p = 6.3*10−5) and Openness (rg = 0.24, p = 0.036), but not with the other personality traits (all | rg | 0.30). A cluster and item-level analysis showed positive genetic correlations of BPD with the Neuroticism clusters “Depressed Affect” and “Worry”, and with a broad range of Neuroticism items (N = 348,219–376,352). PGS analyses confirmed the genetic correlations, and found an independent contribution of the personality traits to BPD risk. The observed associations indicate a partially shared genetic background of BPD and the personality traits Neuroticism and Openness. Larger GWAS of BPD and the “Big Five” are needed to further explore the role of personality traits in the etiology of BPD.

Abstract Increased risk-taking is a central component of bipolar disorder (BIP) and is implicated in schizophrenia (SCZ). Risky behaviours, including smoking and alcohol use, are overrepresented in both disorders and associated with poor health outcomes. Positive genetic correlations are reported but an improved understanding of the shared genetic architecture between risk phenotypes and psychiatric disorders may provide insights into underlying neurobiological mechanisms. We aimed to characterise the genetic overlap between risk phenotypes and SCZ, and BIP by estimating the total number of shared variants using the bivariate causal mixture model and identifying shared genomic loci using the conjunctional false discovery rate method. Summary statistics from genome wide association studies of SCZ, BIP, risk-taking and risky behaviours were acquired (n = 82,315–466,751). Genomic loci were functionally annotated using FUMA. Of 8.6–8.7 K variants predicted to influence BIP, 6.6 K and 7.4 K were predicted to influence risk-taking and risky behaviours, respectively. Similarly, of 10.2–10.3 K variants influencing SCZ, 9.6 and 8.8 K were predicted to influence risk-taking and risky behaviours, respectively. We identified 192 loci jointly associated with SCZ and risk phenotypes and 206 associated with BIP and risk phenotypes, of which 68 were common to both risk-taking and risky behaviours and 124 were novel to SCZ or BIP. Functional annotation implicated differential expression in multiple cortical and sub-cortical regions. In conclusion, we report extensive polygenic overlap between risk phenotypes and BIP and SCZ, identify specific loci contributing to this shared risk and highlight biologically plausible mechanisms that may underlie risk-taking in severe psychiatric disorders.

Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we extended the Multivariate Omnibus Statistical Test (MOSTest) and applied it to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology robustly replicated in 8,060 children of mixed ethnicity from the Adolescent Brain Cognitive Development (ABCD) Study®. This reflects more than 8-fold increase in genetic discovery at no cost to generalizability compared to the commonly used univariate GWAS methods applied to region of interest (ROI) data. Functional follow up including gene-based analyses implicated 10% of all protein-coding genes and pointed towards pathways involved in neurogenesis and cell differentiation. Power analysis indicated that applying the MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. The large boost in power obtained with the vertex-wise MOSTest together with pronounced replication rates and highlighted biologically meaningful pathways underscores the advantage of multivariate approaches in the context of highly distributed polygenic architecture of the human brain.

In the adult brain, apolipoprotein E (apoE) mRNA is thought to be expressed by nonneuronal cells. Yet, when a brain damage has occurred, the protein is found in neurons. We have studied apoE expression following systemic kainic acid (KA), injected in rats to induce hippocampal neurodegeneration. We describe two effects. First, a moderate increase of apoE levels in astrocytes. Second, and unexpected, a very strong increase of apoE mRNA levels in clusters of CA1 and CA3 pyramidal neurons. Neuronal identity of these cells is supported by a series of observations. First, apoE hybridization signals were found in cells with morphological characteristics of pyramidal neurons. Second, the cells were positive for the neuronal marker MAP2. Third, the cells were negative for the astrocytic marker GFAP and for the microglia marker OX42. Fourth, the same distribution pattern was found with probes hybridizing to c-fos, a transcription factor transiently expressed in neurons under stress. At 48 and 72 h following KA, most of the excitotoxic cell death had already occurred. Since no morphological signs of programmed cell death were observed in apoE-positive pyramidal neurons, we suggest that expression of apoE by neurons may be part of a rescue program to counteract neurodegeneration.