Table_1_Neurofilament-Light Chain as Biomarker of Neurodegenerative and Rare Diseases With High Translational Value.XLSX (13.78 kB)

Table_1_Neurofilament-Light Chain as Biomarker of Neurodegenerative and Rare Diseases With High Translational Value.XLSX

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posted on 11.06.2020, 04:06 by Tina Loeffler, Irene Schilcher, Stefanie Flunkert, Birgit Hutter-Paier

Neurofilament-light chain (NF-L) is a well-known clinical biomarker of many neurodegenerative diseases. By analyzing amyotrophic lateral sclerosis (ALS) patients cerebrospinal fluid (CSF) or plasma, progression of NF-L levels can forecast conversion from the presymptomatic to symptomatic stage and time of survival. The use of plasma for NF-L measurement makes this biomarker exceptionally valuable for clinical studies since sample collection can be performed repeatedly without causing much harm. Detailed analyses of NF-L expression in neurodegenerative disease patient’s samples were already performed, while NF-L levels of preclinical models of ALS, Alzheimer’s and Parkinson’s disease as well as lysosomal storage diseases are still widely unknown. We therefore evaluated NF-L levels in the plasma of the ALS models SOD1-G93A low expressor and TAR6/6 mice, the Alzheimer’s disease (AD) model 5xFAD, the Parkinson’s disease model Line 61 and the Gaucher disease (GD) model 4L/PS-NA and the CSF of selected models. Our results show that NF-L levels are highly increased in the plasma of ALS, Alzheimer’s and GD models, while in the analyzed Parkinson’s disease model NF-L plasma levels barely changed. Most analyzed models show a progressive increase of NF-L levels. NF-L measurements in the plasma of the neurodegenerative disease mouse models of ALS and AD are thus a good tool to evaluate disease progression. Compared to analyses in human tissues, our results suggest a high translation value of murine NF-L levels and their progression. Furthermore, our data indicate that NF-L might also be a good biomarker for disorders with a neuronal component like some lysosomal storage diseases.

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