Maja Jagodic

This study identifies genetic loci associated with early MS severity using genome-wide association analysis and finds candidate effector genes and pathways.

This study identifies X-chromosome hypomethylation in female MS patients and links it to XCI escape genes and immune processes.

This paper uses 6-base sequencing to analyze DNA modifications in cerebrospinal fluid cell-free DNA, providing insights into neurodegenerative biology for liquid biopsy applications.

The paper uses single-cell sequencing to show coordinated immune-cell changes between blood and CSF in early MS, with CSF enrichment of memory T-cells and B-cells and depletion of cytotoxic populations.

This study develops CRISPR-based mouse lines for locus-specific DNA methylation editing and shows locus-dependent transcriptional effects in vivo.

GeneSetCluster 2.0 improves gene-set analysis by reducing redundancies, enhancing computational efficiency, and providing accessible tools for both programmers and non-programmers.

This study shows that human amniotic epithelial cells reduce CNS inflammation in MS by inducing immunosuppressive myeloid cells and resolving inflammation.

The paper profiles histone modifications in adult human CNS cells, revealing epigenetic memory of developmental programs in oligodendroglia.

The paper profiles small non-coding RNAs in multiple compartments of MS patients and controls, identifying distinct sncRNA expression patterns in CSF and PBMCs that suggest organ-specific regulatory mechanisms.

The paper introduces a conceptual framework and bioinformatics pipeline for multi-omics data integration, validated on TCGA datasets to enhance feature identification compared to single-omics analysis.

The paper benchmarks disease module identification methods using GWAS and validates a multi-omic module strongly associated with multiple sclerosis risk factors.

This study identifies Gsta4 as a regulator of apoptosis in adult oligodendrocyte differentiation and remyelination, showing its role in modulating the Fas/Casp8/Bid mitochondrial axis.

The paper develops a mathematical model combining mRNA splice variants and time-delay to predict protein abundance from RNA-Seq, improving biomarker discovery in immune diseases.

The paper identifies low-frequency coding variants contributing to multiple sclerosis risk using a large case-control study.