Rachel J. Saunders-Pullman

This paper uses a deep learning model to identify genetic variants associated with isolated focal dystonia by leveraging neuroimaging endophenotypes.

This study uses single-cell RNA sequencing and TCR profiling to analyze immune changes in Parkinson's disease across different stages and identifies sex-dependent immune alterations and TCR diversity.

This study shows the G2019S LRRK2 mutation alters transcriptomes of myeloid cells under proinflammatory conditions, affecting lipid metabolism and phagocytic function.

This study conducts a genome-wide association study of copy number variations in Parkinson's disease, identifying a significant PRKN deletion but limited replication in an independent dataset.

The paper identifies integrated stress response (ISR) signatures and proteostasis defects in monocytes from GBA1- and LRRK2-linked Parkinson's disease, linking them to immune dysfunction.

BATL is a Bayesian classifier for targeted lipidomics that annotates LC-ESI-MS/MS peaks with high accuracy using eight features, achieving over 95% correct identification in SRM datasets.

The paper identifies discordant mitochondrial gene expression patterns in PD monocytes and microglia, revealing distinct transcriptomic alterations in these myeloid cell types.

This study identifies genetic modifiers of LRRK2 mutations in Parkinson's disease, finding a significant variant in CORO1C and a polygenic risk score effect on penetrance.