Markus Otto

The paper identifies the CSF YWHAG:NPTX2 ratio as a biomarker for predicting clinical severity and phenoconversion in FTLD, showing strong correlation with disease progression and improved trial design potential.

This paper uses machine learning to stratify genetic frontotemporal dementia patients into subtypes and provides progression scores that improve trial enrichment efficiency.

This study shows HSV infection increases ALS risk and promotes TDP-43 pathology through ICP0-mediated disruption of PML bodies.

The paper develops an MRI-based machine learning classifier to identify presymptomatic C9orf72 carriers at high risk of disease onset within two years.

The paper shows that white matter hyperintensities (WMHs) appear before other biomarkers in GRN-related frontotemporal dementia, suggesting they are early indicators of disease progression.

The paper identifies a monocyte dysregulation signature in MDD linked to clinical symptoms using CITE-Seq data from PBMCs.

This study examines the interactions between A{beta}, tau, LATE-NC, -synuclein, and APOE {varepsilon}4 in 480 post-mortem brains, finding that tau is the strongest predictor of neurodegeneration while LATE-NC primarily affects hippocampal neuron loss.

The paper validates EV isolation from multiple biofluids using orthogonal methods but finds L1CAM does not reliably enrich for neuron-derived EVs.

This study shows that amygdala-predominant α-synuclein pathology is linked to reduced hippocampal neuron density in Alzheimer's disease, mediated through pTau and LATE-NC.

This study investigates the association between cerebellar and subcortical atrophy and neuropsychiatric symptoms in genetic frontotemporal dementia, finding significant differences across genetic mutations.

This study shows that atrophy patterns in bvFTD are shaped by both global brain network structure and local transcriptomic vulnerability from disease-related genes.

The paper investigates the relationship between gene expression and brain atrophy in genetic frontotemporal dementia, finding correlations between atrophy patterns and specific gene sets related to vascular, glial, and neuronal functions.

The paper develops a random forest classifier to diagnose behavioral variant frontotemporal dementia using MRI and cognitive scores, achieving high accuracy in both training and validation cohorts.