Vera Fominykh

The paper identifies shared genetic variants between major psychiatric disorders and retinal traits, revealing molecular mechanisms linking retinal morphology to neurodevelopmental and neurotransmission processes.

Bivariate GSA-MiXeR is a tool that models genetic correlations between two traits to identify genomic regions associated with psychiatric and neurodegenerative disorders using single-cell RNA sequencing data.

This study analyzes GWAS data from nearly 1 million cases to show widespread genetic overlap between neurological and psychiatric disorders, with shared biological processes and divergent effect sizes.

This study identifies 118 new genetic loci associated with Alzheimer's disease across diverse ancestries and discovers 48 novel risk loci, including those enriched in neuronal cell types.

This study maps the genetic continuum of autoimmune and autoinflammatory disorders using GWAS and statistical methods, identifying four genetic clusters with potential implications for treatment.

This study identifies shared genetic loci between common epilepsies and general cognitive ability using LDSC, MiXeR, and conjFDR analyses.

The paper introduces trivariate MiXeR to quantify genetic overlap between three complex phenotypes using GWAS summary statistics, demonstrating its ability to detect complex patterns of genetic overlap.