Héléna A. Gaspar

Evaluation of Polygenic Prediction Methodology within a Reference-Standardized Framework

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

A phenome-wide association and Mendelian Randomisation study of polygenic risk for depression in UK Biobank

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.

Genetic Identification of Cell Types Underlying Brain Complex Traits Yields Novel Insights Into the Etiology of Parkinson's Disease

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.

Shared Genetic Risk between Eating Disorder- and Substance-Use-Related Phenotypes: Evidence from Genome-Wide Association Studies

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

A major role for common genetic variation in anxiety disorders

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

Comparative genetic architectures of schizophrenia in East Asian and European populations

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.

Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders

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.

The genetics of the mood disorder spectrum: genome-wide association analyses of over 185,000 cases and 439,000 controls

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

Genetic variation in the Major Histocompatibility Complex and association with depression

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.

Variably methylated regions in the newborn epigenome: environmental, genetic and combined influences

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.

Genetic comorbidity between major depression and cardio-metabolic disease, stratified by age at onset of major depression.

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

Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank

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.

Genomewide association study identifies 30 loci associated with bipolar disorder

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

Using genetic drug-target networks to develop new drug hypotheses for major depressive disorder

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

Probabilistic ancestry maps: a method to assess and visualize population substructures in genetics

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.

Navigome: Navigating the Human Phenome

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

Applying polygenic risk scoring for psychiatric disorders to a large family with Bipolar Disorder and Major Depressive Disorder

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

Genetic Identification Of Brain Cell Types Underlying Schizophrenia

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 analyses identify 44 risk variants and refine the genetic architecture of major depression

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.

Functional consequences of genetic loci associated with intelligence in a meta-analysis of 87,740 individuals

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

Identifying tissues implicated in Anorexia Nervosa using Transcriptomic Imputation

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

Pathways analyses of schizophrenia GWAS focusing on known and novel drug targets

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