Daniel Felsky

This study links the FREM3 gene to brain and cognitive aging using cross-species evidence from mice and humans, showing reduced brain volume and cognitive performance in Frem3 knockout mice and lower FREM3-GReX associated with reduced brain surface area and cognitive performance in humans.

This study uses Mendelian randomization and mediation analysis to show that neuroticism's link to Alzheimer's disease is mediated by modifiable factors like depression, hypertension, and alcohol consumption, rather than being causal.

The paper investigates polygenic associations between motor behaviour, neuromotor traits, and active music engagement across four cohorts, finding a link between walking pace polygenic scores and music engagement.

The paper uses iPSC-derived astrocytes to study genetic risk factors for Alzheimer's disease, finding concordant molecular changes in both astrocytes and brain tissue.

The paper proposes a method to test causality between genetic variants and brain imaging modalities for Alzheimer's disease using summary statistics from GWAS data.

The paper develops polygenic risk scores for molecular brain aging and links them to cortical thickness and cognitive performance in older adults.

This paper develops an iPSC platform to rapidly generate alpha-synuclein inclusions and investigates their formation, subtypes, and molecular interactions.

The paper develops eigen-polygenic risk scores (ePRSs) from clustered subnetworks of single-trait PRSs and shows they improve prediction of Alzheimer's Disease and related phenotypes.

The paper investigates CHRNA5's role in amyloid pathology in aging and Alzheimer's by analyzing genetic variants and cell-type expression in human brain tissue.

The paper examines correlations between task and resting-state brain signatures of sleep, cognition, and depression in over 30,000 individuals, revealing opposing neural patterns associated with insomnia and depression.

The paper quantifies microglial contamination in Patch-seq datasets and shows its impact on electrophysiological properties of neurons.

The paper tests a polygenic risk score for microglial activation in Alzheimer's disease and aging, finding no significant improvement in predictive power for AD diagnosis or cognitive performance.

The paper analyzes RNA-seq data from Caribbean-Hispanic Alzheimer's patients and controls to identify ancestry-specific gene expression patterns associated with disease.

This paper uses multi-omic integration to identify molecular subtypes of aging in brain tissue, finding subtypes associated with cognitive decline.

The paper identifies glucocorticoid-responsive molecular defects in MS T cells through cell-type-specific transcriptomic profiling and validates potential therapeutic targets.

The paper identifies somatostatin and intra-telencephalic neurons as significantly associated with Alzheimer's disease using bulk and single-nucleus transcriptomics across multiple datasets.

The paper identifies mQTL effects of MS susceptibility loci on DNA methylation in CD4+ T cells, revealing both cis and trans regulatory impacts.

The paper identifies hypometabolic regions in Alzheimer's disease using PET data and links them to transcriptomic changes in a specific donor's brain, highlighting microglia and ribosomal proteins.

This paper performs a large-scale eQTL meta-analysis across cerebral cortical and cerebellar brain regions, identifying distinct eQTL patterns and demonstrating improved power over existing studies.

The paper examines microglial activation in elderly brains, finding strong associations with neuropathology and cognitive decline, and identifies genetic overlaps with Alzheimer's disease.

The paper identifies gene modules in human frontal cortex microglia associated with beta-amyloid and tau pathology in Alzheimer's disease.