Aiden Peter Corvin

Ultra-rare damaging coding variants in 87,959 schizophrenia cases and 150,587 controls implicate 40 genes (16 exome-wide, 24 at 5% FDR), half overlapping autism, developmental delay or bipolar genes.

BICEP extends its Bayesian model to include indels and copy number variants for rare variant prioritization in pedigrees, showing comparable performance to the original single nucleotide variant model.

The paper introduces co-expression-based models to improve eQTL predictions and identifies novel schizophrenia-associated genes using brain RNA-seq data.

The paper introduces dGAMLSS, a distributed algorithm for fitting GAMLSS models to construct population reference charts without sharing patient data.

The paper analyzes over 800,000 human genomes to assess penetrance of clinically relevant variants, finding that 95% of pLoF variants in severe diseases have explanations for lack of disease manifestation.

This study identifies a schizophrenia-associated radial glia cell state that disrupts early human brain development through single-cell transcriptomic and epigenomic analyses of organoids.

This study identifies two ASD subgroups with distinct brain morphology using cross-cultural datasets, highlighting key brain regions associated with subgroup characteristics and autistic traits.

The paper identifies novel CNV loci and dose-dependent gene effects across six psychiatric disorders using genome-wide analysis.

The paper identifies shared and divergent genetic mechanisms across psychiatric disorders using gene-set burden analysis of copy number variants.

The paper identifies MEF2C direct target genes enriched for schizophrenia and cognitive function genes, showing their involvement in neurogenesis and mitochondrial function.

The paper uses brain cell-type-specific protein interactomes to interpret genetic data in schizophrenia and identifies enriched networks and genes associated with the disease.

Exomes of 24,248 schizophrenia cases and 97,322 controls implicate ultra-rare damaging variants in 10 genes, including GRIN2A and GRIA3, with odds ratios of 3 to 50.

The paper introduces brain charts as a standardized resource for benchmarking brain morphology across the human lifespan using MRI data from a large and diverse cohort.

This paper identifies potential nootropic drug targets by integrating large-scale cognitive GWAS and transcriptomic data to find credible druggable genes.

The paper compares ten polygenic score methods for psychiatric disorders across multiple cohorts, finding that some methods significantly improve prediction statistics over the baseline PC+T method.

The paper reports exome sequencing findings in bipolar disorder, identifying AKAP11 as a shared risk gene with schizophrenia through ultra-rare protein-truncating variants.

The paper identifies MeCP2 target genes associated with multiple brain disorders and shows they share common molecular mechanisms in neuronal transmission, immunity, and development.

This study identifies DNA methylation changes in blood samples from psychosis patients, including treatment-resistant schizophrenia, and links them to biological age, smoking, and cellular composition.

The paper uses pleiotropic meta-analysis to identify genetic loci associated with cognition, education, and schizophrenia, revealing distinct biological mechanisms for concordant and discordant genetic correlations.

The paper links reduced cortical morphometric similarity in psychosis to the expression of schizophrenia-related genes in specific brain regions.

This paper conducts a GWAS on suicide attempt across psychiatric disorders, identifying genetic loci and showing polygenic risk for major depression predicts suicide attempt in multiple disorders.

The paper finds a genetic association between schizophrenia risk and age at first birth in women, with different genetic correlations in younger and older age groups.

This study identifies 206 new genomic loci and 1,041 genes associated with intelligence using a large GWAS meta-analysis of 279,930 individuals.

This study compares LDSC and GREML methods for estimating genetic correlation, showing GREML provides higher accuracy, especially in the presence of genetic heterogeneity.

The paper identifies an excess of rare loss-of-function and missense mutations in voltage-gated sodium channels and synaptic genes associated with schizophrenia using large-scale sequencing and meta-analysis.

This study performs a large-scale GWAS of cognitive ability, identifies 70 genomic loci, and finds tissue-specific gene expression and potential drug targets.

The paper confirms a polygenic effect on negative symptoms in schizophrenia using GWAS, identifies novel loci, and highlights the need for larger samples.

This paper investigates how global polygenic risk scores, sex, and their interaction predict schizophrenia risk using a classification model, finding sex and polygenic risk are the strongest predictors.