Mathew J. Koretsky

This study investigates the role of SORL1 genetic variants in AD, RD, and PD across diverse populations, identifying variants associated with risk but no significant cumulative effect.

This study identifies genetic variants associated with Alzheimer's disease and frontotemporal dementia in admixed Latin American populations using whole-genome sequencing and ancestry analysis.

CNV-Finder uses deep learning to detect copy number variations from array data, improving accuracy and reducing manual workload for downstream analyses.

CARDBiomedBench evaluates LLM performance in biomedical research using a benchmark focused on neurodegenerative diseases, revealing significant limitations in response quality and safety.

This study identifies genetic variants associated with Parkinson's disease in African and African admixed populations, highlighting differences from European and Asian populations.

MoVUS, a random forest model, classifies variants of uncertain significance in Alzheimer's and neurological disorders with high accuracy, prioritizing potentially pathogenic variants.

The paper identifies the LRRK2 p.A419V variant as a significant risk factor for Parkinson's disease in East Asian populations and explores its association with age of onset.

This paper analyzes genetic variation in Parkinson's disease across multiple ancestries, revealing ancestry-specific patterns and highlighting the importance of diverse populations in genetic research.

This study compares polygenic risk scores for Parkinson's disease across seven ancestries, finding varying predictive accuracy and highlighting the need for ancestry-specific models.

The paper evaluates the NeuroBooster array's performance in genotyping pathogenic variants in Parkinson's disease across ancestries and validates their frequencies in diverse populations.

GenoTools provides a Python package for genotype data QC, ancestry estimation, and GWAS, enabling scalable and reproducible analysis of large genetic datasets.

The paper introduces the NeuroBooster Array, a genome-wide genotyping platform designed to study neurological disorders across diverse populations by capturing genetic variation and enabling imputation of disease-related variants.

Cluster Buster improves SNP genotyping quality by reducing no-calls and enhancing genotype accuracy for neurodegenerative disease research.

The paper identifies druggable target genes for neurodegenerative diseases using Mendelian Randomization and provides a web platform for exploring therapeutic targets.

Intronic GBA1 variant rs3115534-G, common in African and African admixed ancestry but rare elsewhere, raises Parkinson's disease risk (OR 1.58) and lowers onset age.

This study clusters patients with neurodegenerative diseases based on genetic risk variants, revealing overlapping genetic etiology and subsets with no common risk factors.

The paper examines how a polygenic Parkinson's disease genetic risk score modifies the risk of parkinsonism in Gaucher disease patients.

This paper applies Aligned-UMAP to longitudinal biomedical datasets to reveal time-dependent patterns and provides best practices for its use.