Antonio F. Pardiñas

This study identifies genetic variants differentially associated with schizophrenia and bipolar disorder using CC-GWAS, finding 19 loci with divergent effects and biological themes related to neuronal function.

This paper applies FINEMAP and SuSiE to fine-map schizophrenia risk loci, identifying new genes with high concordance between methods and validating them using LoFI and rare variant enrichment.

This study quantifies pharmacogenomic effect sizes for psychiatric drugs, finding larger effects for proximal outcomes like bioavailability than distal outcomes like efficacy and toxicity.

The paper examines how genetic risk for physical health conditions affects comorbidities in individuals with severe mental illness, finding stronger genetic associations than psychiatric risk factors.

This paper introduces SuSiEx, a cross-population fine-mapping method that improves resolution and power by integrating data across ancestries, leading to more accurate identification of causal variants in complex traits and diseases.

This study identifies rare genetic variants in pharmacogenes that influence clozapine metabolism in schizophrenia patients, with CYP1A2 variants showing the strongest effect.

The paper identifies a striatal gene set linked to schizophrenia risk that predicts in vivo dopamine synthesis and striatal activation in neurotypical and patient cohorts.

This study identifies aberrant CPEB4 splicing and downstream mis-expression of SCZ-risk genes as a novel etiological mechanism in schizophrenia.

This study investigates the role of Neanderthal introgression and natural selection in the heritability of neurodegenerative diseases and finds no significant contribution from either.

A genome-wide association study of 69,369 schizophrenia cases and 236,642 controls identifies 270 risk loci, prioritizes 130 genes, and links common and rare risk variants to neuronal synaptic biology.

This study identifies neurogenic transcriptional programs linked to neuropsychiatric disorders and cognition using DLG2 knockout models and transcriptomic data.

The paper examines the developmental expression of genes related to voltage-gated cation channels and their association with psychiatric disorders, finding that gene expression patterns vary with age and disorder type.

The paper examines the genetic association of FMRP targets with schizophrenia, major depressive disorder, and bipolar disorder, finding enrichment for risk alleles and variants in these disorders.

This study performs a transcriptome-wide association study to link schizophrenia risk variants to gene expression in the dorsolateral prefrontal cortex, identifying 89 genes associated with pre- and post-synaptic abnormalities.

This study conducts the largest genetic association analysis of psychotic experiences in the UK Biobank, identifying four genome-wide significant loci and showing shared genetic risk with schizophrenia, depression, bipolar disorder, and neurodevelopmental disorders.

This study integrates ASD GWAS summary statistics with gene expression data to identify differentially expressed genes in ASD and estimate heritability explained by predicted expression.

The paper analyzes rare and common alleles in schizophrenia trios, identifying rare missense variants in SLC6A1 and confirming the role of neurodevelopmental disorder genes.

This study uses conditional GWAS analysis to identify disorder-specific SNPs for psychiatric disorders, finding some variants with reduced pleiotropy effects.

This study examines the medical consequences of pathogenic CNVs in adults using UK Biobank data, finding significant associations between CNVs and various health outcomes.

The paper maps schizophrenia-associated genomic loci to specific brain cell types using single-cell RNA-sequencing data, finding consistent enrichment in pyramidal cells, medium spiny neurons, and interneurons.

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.

The paper uses transcriptomic imputation to identify schizophrenia risk genes across multiple brain regions, finding 71 associated genes and 36 enriched pathways.

The paper investigates the relationship between polygenic risk scores for schizophrenia and psychotic features in bipolar disorder, finding a gradient of genetic liability based on the level of mood-incongruent symptoms.