Josefin Werme

The paper identifies five genomic factors explaining most genetic variance across 14 psychiatric disorders and finds shared and disorder-specific genetic signals with distinct biological functions.

The paper uses GWEIS and in silico methods to study gene-environment interactions in alcohol misuse, identifying SES-modulated genes and highlighting challenges in detecting molecular GxE effects.

This study shows that interpreting TWAS results as evidence of genetic relationships between gene expression and phenotypes leads to inflated type 1 errors and unreliable conclusions.

This study uses local genetic correlation analysis to link depression with molecular and brain imaging endophenotypes, identifying potential genes and mechanisms involved in major depressive disorder.

This study identifies genes associated with structural and functional connectivity in resting-state networks and finds genetic overlap within functional domains.

This study investigates genetic overlaps between 12 psychiatric disorders, identifying pleiotropic SNPs and biological pathways, but finds challenges in interpreting shared mechanisms due to varying genetic architectures.

LAVA analyzes local genetic correlations between multiple traits and demonstrates heterogeneous patterns across the genome that are masked by global analyses.