Karen E. Morrison

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.

This paper develops a deep learning model using SNP microarray data to predict ALS risk with high accuracy across diverse populations and genotyping platforms.

The paper investigates oligogenic risk in ALS using genome sequencing data, finding that multiple rare variants in known ALS genes increase disease risk but not clinical outcomes.

The paper introduces a method to compress genetic data using autoencoders that leverage linkage disequilibrium structure, achieving high reconstruction accuracy while reducing data size.

This study analyzes genetic and clinical data from PLS patients to assess the role of genetic testing and identify potential disease-associated variants.

This study investigates the role of Neanderthal introgression and natural selection in the heritability of neurodegenerative diseases and finds no significant contribution from either.

The paper analyzes CAV1 and CAV2 expression in ALS brain tissue and finds higher expression in ALS patients, associated with increased survival and slower disease progression.

This study identifies NEFH tail domain mutations as risk factors for ALS through meta-analysis and variant burden analysis in case-control studies and whole-genome sequencing data.

This study identifies 690 candidate ALS genes using a hierarchical Bayesian model, highlighting genetic convergence on the distal axon and functional significance in motor neurons.

The paper identifies de-novo SPTLC1 mutations in juvenile ALS patients and suggests serine supplementation may alleviate symptoms.

The paper identifies an enrichment of rare protein-truncating variants in ALS patients, highlighting novel genes like DNAJC7 and known ALS genes such as SOD1, NEK1, and FUS.

This study conducts a GWAS of Parkinson disease in Spain, identifies a novel population-specific signal at PARK2 associated with age-at-onset, and highlights genetic substructure for future fine-mapping.

Project MinE analyzes whole-genome sequencing data from ALS patients and controls to study genetic variation and its implications for disease susceptibility.

The paper introduces ExpansionHunter, a tool for detecting long repeat expansions from PCR-free WGS data, achieving high sensitivity and specificity in identifying pathogenic expansions.