Cornelis Blauwendraat

SALRR provides a scalable platform for long-read RNA-seq analysis, identifying novel splice variants in human brain tissue.

The paper characterizes the genetic landscape of Parkinson's disease in a Chilean cohort, identifying common pathogenic variants in LRRK2 and GBA1.

This study uses long-read sequencing to map transposable element variation in human brain tissue, revealing regulatory and epigenetic effects across cell types and ancestries.

This study identifies pathogenic and intermediate repeat expansions in Parkinson's disease and parkinsonism across 11 ancestries, highlighting ATXN2's role in PD risk and ancestry-specific patterns.

This paper uses long-read sequencing to analyze haplotype-resolved DNA methylation at the APOE locus in brain samples, identifying allele-specific methylation patterns linked to Alzheimer's disease risk.

The paper generates a collection of 65 isogenic human stem cell lines with PD-associated mutations to study Parkinson's disease, revealing that most genetic variation comes from cell culture rather than genome editing.

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 introduces a genome browser for Parkinson's disease genomic data, integrating WGS and CES samples with variant annotations and ancestry stratification.

The paper generates and characterizes a custom genome assembly for the KOLF2.1J iPSC line to improve genomic analysis accuracy compared to standard references.

The paper identifies rare noncoding variants associated with Parkinson's disease using multi-omic data from over 3.3 million nuclei.

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

This study identifies genetic associations between lysosomal genes and Parkinson's disease risk across diverse populations using GWAS and whole genome sequencing data.

The paper identifies FGF14 GAA repeat expansions in Parkinson's disease using long-read sequencing and finds they occur in both patients and controls.

The paper assesses the frequency of dystonia-linked pathogenic variants in Parkinson's disease patients and finds they are present in 0.57% of cases, with GCH1 being the most common gene affected.

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 USP18 as a negative regulator of interferon response at a lupus risk locus through trans-eQTL analysis in lymphoblastoid cell lines.

The paper uses long-read sequencing to analyze genomic and epigenomic changes in melanoma subclones, revealing parallel evolutionary paths and lineage-specific methylation patterns.

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 investigates how GBA1 mutations affect glycoprotein nonmetastatic melanoma protein B (GPNMB) expression in dopaminergic neurons, linking lipid accumulation to Parkinson's disease risk.

The paper investigates the biological impact of GBA1 mutations using multi-omics in isogenic iPSC lines, finding limited overlapping results across cell types and suggesting RNA-based quantitation may not be optimal for characterizing GCase mechanisms.

This study performs APOE-stratified GWAS to uncover genetic mechanisms underlying Alzheimer's disease risk and response to therapies.

This paper prioritizes Parkinson's disease risk genes in GWAS loci using a polygenic priority score, identifying 46 genes with potential for therapeutic development.

The paper introduces the Neurodegenerative Disease Knowledge Portal (NDKP), an open-science platform aggregating genomic datasets for neurodegenerative diseases to enable collaborative analysis and discovery.

The paper uses long-read sequencing to identify structural variants and their impacts on gene expression and methylation in diverse human brain samples.

This study identifies genetic correlations between hyposmia and Parkinson's disease, finding a strong causal link from PD to hyposmia but weaker evidence for the reverse.

The paper identifies a non-coding risk variant in GBA1 associated with Parkinson's disease in African ancestry populations, showing it disrupts splicing and reduces glucocerebrosidase activity.

The paper shows ancestry-specific gene expression in monocytes mediates neurodegenerative disease risk through innate immune cell expression of neurodegeneration-related genes.

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

The paper identifies decreased SNCA expression in Parkinson's Disease blood samples after correcting for immune cell effects, suggesting it as a potential transcriptomic biomarker.