Héléna A. Gaspar

This study evaluates polygenic scoring methods in a reference-standardized framework, finding that LDPred2, lassosum, and PRScs provide the best predictive performance.

This study identifies traits associated with polygenic risk for depression using UK Biobank data and finds causal links between depression risk and brain structure, as well as environmental interactions.

This study identifies cell types associated with brain complex traits using GWAS and single-cell transcriptomics, revealing novel roles for oligodendrocytes in Parkinson's disease.

The paper estimates genetic correlations between eating disorder and substance-use-related phenotypes using GWAS data, finding both positive and negative associations.

This study identifies five novel genome-wide significant loci for anxiety disorders and finds significant genetic correlations with depression, insomnia, and coronary artery disease.

This study identifies schizophrenia genetic associations in East Asian and European populations, finding similar genetic effects across ancestries but highlighting challenges in polygenic risk prediction across groups.

The paper examines common genetic variants' contribution to bipolar disorder risk in multiplex families and finds higher polygenic risk scores in affected individuals compared to controls and unaffected family members.

This study identifies 73 genome-wide significant loci for mood disorders, revealing shared and distinct genetic factors between major depressive disorder and bipolar disorder.

This study investigates whether genetic variation in the Major Histocompatibility Complex (MHC) is associated with depression risk, finding no significant associations at a conservative threshold.

The paper examines how genetic and environmental factors influence DNA methylation at variably methylated regions in neonatal blood, finding that combined effects best explain methylation variability.

This study investigates genetic associations between major depression and cardio-metabolic traits, finding shared genetic aetiology regardless of depression onset age.

This study investigates the genetic and environmental links between major depressive disorder and traumatic experiences using UK Biobank data, finding shared genetic factors and distinct patterns in trauma-exposed individuals.

This study identifies 30 genome-wide significant loci associated with bipolar disorder, including novel genes involved in ion channels, neurotransmitters, and synaptic components.

This paper uses GWAS data from MDD to identify potential drug targets and repurposing opportunities by analyzing drug-target networks and gene expression effects.

This paper introduces GTM for ancestry classification and visualization, showing it can better capture ancestry substructures than PCA by estimating class probabilities and explaining more variance.

The paper constructs a phenome map using genetic correlations from 465 GWAS to cluster human traits and identify pathway enrichments.

The paper applies polygenic risk scoring to a large family with bipolar and depressive disorders to study genetic risk patterns and anticipation.

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.

Genome-wide association meta-analysis of 130,664 major depression cases and 330,470 controls identifies 44 independent risk loci enriched in cortical neurons, conserved mammalian regions, splicing networks, and antidepressant targets.

The paper identifies brain cell types and genes associated with intelligence using GWAS and single-cell gene expression data from a large cohort.

This paper uses transcriptomic imputation to identify gene-tissue associations linked to Anorexia Nervosa risk, finding significant links in both brain and metabolic tissues.

This study analyzes schizophrenia GWAS data to identify drug targets and pathways, finding significant enrichment for known antipsychotics and novel therapeutic opportunities.