John Ravits

This paper evaluates combining expression-based surrogate variables and genotype-based principal components in differential expression analysis, finding the combined approach improves replicability and biological recall in ALS datasets.

This study investigates how SARS-CoV-2 N-protein forms biomolecular condensates and interacts with ALS-associated RNA-binding proteins in vitro and human cell models.

This study identifies mitochondrial-derived double-stranded RNA as a source of RNA stress in aged neurons, which activates the ISR through PKR and contributes to neurodegeneration.

This study identifies acetylation of lysine 82 in TDP-43 as a mechanism causing nuclear loss of function and cytoplasmic accumulation, linked to neurodegenerative diseases like ALS.

This paper demonstrates that transient suppression of PTBP1 in aged glial cells can re-activate neurogenesis in murine and human brains, generating new neurons through canonical pathways.

The paper analyzes single-nucleus RNA-seq data from human spinal cord neurons, identifies motor neurons as rare, and highlights discrepancies with a prior study due to potential misclassification of cholinergic debris.

The paper identifies rare somatic mutations in sporadic ALS and FTD cases, suggesting they contribute to disease and widespread neurodegeneration.

The paper investigates C9orf72 expansion carriers using radiogenomics to link peripheral blood transcriptomics with thalamic atrophy and clinical impairment, finding global transposable element de-repression and associations between C9orf72 expression and disease severity.

The paper compares TDP-43's transcriptional and splicing effects in muscle and neuronal cells, showing tissue-specific roles in disease.

The paper identifies ELAVL3 as a downregulated RNA binding protein in ALS, showing nuclear depletion and mislocalization in motor neurons, with findings suggesting loss of function rather than cytoplasmic toxicity.

The paper uses single-cell RNA-seq to identify early ALS signatures in iPSC-derived motor neurons across multiple models and platforms.

This study identifies metabolic defects in ALS motor neurons and shows that nicotinamide and SIRT3 activation can rescue these defects.

The paper uses unsupervised machine learning to identify three molecular subtypes in ALS cortex samples, associated with oxidative stress, retrotransposon activation, and glial activation.