A polygenic burden of rare disruptive mutations in schizophrenia

By analyzing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we have demonstrated a polygenic burden primarily arising from rare (<1/10,000), disruptive mutations distributed across many genes. Especially enriched genesets included the voltage-gated calcium ion channel and the signaling complex formed by the activity-regulated cytoskeleton-associated (ARC) scaffold protein of the postsynaptic density (PSD), sets previously implicated by genome-wide association studies (GWAS) and copy-number variation (CNV) studies. Similar to reports in autism, targets of the fragile × mental retardation protein (FMRP, product of FMR1) were enriched for case mutations. No individual gene-based test achieved significance after correction for multiple testing and we did not detect any alleles of moderately low frequency (~0.5-1%) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene mapping paradigms in neuropsychiatric disease

Action Identification Characteristics and Priming Effects in ChatGPT

Action Identification Theory (Act ID) refers to the traits and mental processes behind how people think about and describe actions in more concrete terms, called Lower-Level Action Identities, or more abstract terms, called Higher-Level Action Identities. Optimal Act ID use is associated with a variety of communicational and conversational goals and outcomes, and is deeply embedded in the structure of human language. ChatGPT is a Large Large Model (LLM)-driven Conversational AI Chatbot, trained on patterns of language and conversational dynamics, including actions and descriptions of actions at different levels of concreteness and abstraction. ChatGPT is therefore a suitable subject for novel forms of Act ID research. Across 3 pre-registered studies, the Behavior Identification Form was used to assess: 1) ChatGPT’s ability to Apply Act ID (Study 1); To measure its default Act ID level (Study 2); and to evaluate its susceptibility to priming-like effects (Study 3). Results revealed that ChatGPT: 1) Can learn and apply Act ID (r = 1.0, p &lt; .000); 2) Displays a high-level default Act ID (M = 20.72, SD = .79); and 3) Can be experimentally induced to select more or fewer lower- or higher-level identities via simple tasks inspired by human research. These findings hold significant implications for optimal human-AI interactions, raise critical questions about the intelligence and safety of these virtual agents, help further our understanding of how Psychological theories and models can improve the study and development of these applications, and may contribute to the broader study of the human mind and consciousness

A map of human genome variation from population-scale sequencing

The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother-father-child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately 10−8 per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites. These methods and public data will support the next phase of human genetic researc