Isabelle Le Ber

This study uses optical genome mapping to analyze C9orf72 repeat expansion instability in blood from ALS and FTD patients, finding age-dependent differences in repeat size dynamics between conditions.

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.

Skeletal muscle from individuals at elevated genetic risk for ALS/FTD undergoes progressive metabolic reprogramming far before disease onset.

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.

This study uses whole-genome sequencing to identify new genetic loci and structural variants associated with progressive supranuclear palsy, including novel signals in APOE and H1/H2 haplotype region variants.

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