Ganna Leonenko

The paper uses polygenic risk scores to analyze genetic contributions to neurodegenerative diseases across brain cell types, finding shared and disease-specific genetic risks.

The paper uses plasma proteomics to identify differentially abundant proteins and co-expression modules across Alzheimer's disease stages, highlighting potential biomarkers for early detection.

This study shows that DKK3, a Wnt antagonist elevated in Alzheimer's disease, causes synaptic loss and memory impairment, but its knockdown restores synapse integrity and memory in a mouse model.

This paper estimates SNP-based heritability of Alzheimer's disease across five cohorts, showing it ranges from 38-66%, with microglia genes explaining most of the heritability.

This study identifies genetic resilience factors for Alzheimer's disease by constructing polygenic resilience scores that reduce genetic risk penetrance and correlate with polygenic risk scores in unaffected individuals.

The paper analyzes Alzheimer's disease polygenic risk scores using RNA-sequencing to identify novel biological pathways and common mechanisms between case/control classification and PRS associations.

The paper identifies LACTB2 and PLIN2 as novel AD risk genes through monocyte-specific transcriptome-wide association study.

This paper presents a method to standardize polygenic risk scores across populations and demonstrates its application to Alzheimer's disease risk estimation.

The paper uses a novel gene-based analysis approach to identify three novel genes associated with Alzheimer’s disease using genome-wide association data.

This study finds that genetic risk scores for insomnia and sleep duration differ between bipolar I and II subtypes, suggesting distinct genetic liabilities.

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.