Accumulation of neurofilaments (NFs), the major constituents of the neuronal cytoskeleton, is a distinctive feature of neurological diseases and several studies have shown that soluble NFs can be detected in the cerebrospinal fluid (CSF) of patients with neurological diseases, such as multiple sclerosis and frontotemporal dementia. Here we have used an inducible transgenic mouse model of neurodegeneration, CamKII-TetOp25 mice, to evaluate whether NF-L levels in CSF or blood can be used as a biochemical biomarker of neurodegeneration. Induction of p25 transgene brain expression led to increase in CSF and serum NF-L levels that correlated with ongoing neurodegeneration. Switching off p25 prevented further increases in both CSF and serum NF-L levels and concomitantly stopped the progression of neurodegeneration. The levels of CSF NF-L detected in p25 mice are about 4-fold higher than the CSF levels detected in patients with chronic neurodegenerative diseases, such as symptomatic FTD (bvFTD). In addition, our data indicate that the NF-L detected in CSF is most likely a cleaved form of NF-L. These results suggest that CSF and serum NF-L are of interest to be further explored as potential translational dynamic biomarkers of neurodegeneration or as pharmacodynamics biomarkers at least in preclinical animal studies.
The diagnostic of Amyotrophic lateral sclerosis (ALS) remains based on clinical and neurophysiological observations. The actual delay between the onset of the symptoms and diagnosis is about 1 year, preventing early inclusion of patients into clinical trials and early care of the disease. Therefore, finding biomarkers with high sensitivity and specificity remains urgent. In our study, we looked for peptide biomarkers in plasma samples using reverse phase magnetic beads (C18 and C8) and MALDI-TOF mass spectrometry analysis. From a set of ALS patients (n=30) and healthy age-matched controls (n=30), C18- or C8-SVM-based models for ALS diagnostic were constructed on the base of the minimum of the most discriminant peaks. These two SVM-based models end up in excellent separations between the 2 groups of patients (recognition capability overall classes > 97%) and classify blinded samples (10 ALS and 10 healthy age-matched controls) with very high sensitivities and specificities (>90%). Some of these discriminant peaks have been identified by Mass Spectrometry (MS) analyses and correspond to (or are fragments of) major plasma proteins, partly linked to the blood coagulation.
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