Research on a Potential Biomarker for Hereditary Neurological Disease

In her doctoral thesis, Elīna Kalniņa, a doctoral student at Rīga Stradiņš University (RSU), investigated Charcot-Marie-Tooth disease, the most common of the rare neurological disorders, and neurofilaments (more precisely, neurofilament light chains) as possible biomarkers for predicting disease severity.

Charcot-Marie-Tooth is a hereditary polyneuropathy. The most characteristic symptoms that patients with this disease get the sensory disturbances, muscle weakness in the arms and legs, and foot deformities.

Unfortunately, there is currently no specific treatment available for the disease and there are a number of challenges to consider when researching and finding what a specific therapy might entail.

These include the high clinical and genetic variability of the disease, the slow progression of the disease, and the tools available to assess clinical outcome, including the lack of proven biomarkers.

This study describes the clinical, genetic, and diagnostic characteristics in a cohort of hereditary peripheral polyneuropathy patients in Latvia and evaluates neurofilaments as a potential biomarker.

The data of the study shows that neurofilament levels are a promising biomarker for Charcot-Marie-Tooth disease: neurofilament levels are significantly higher in patients with this disease compared to the control group, and neurofilament levels are associated with the severity of Charcot-Marie-Tooth disease. In the future, neurofilaments could be used individually or in combination with other markers as a biomarker for Charcot-Marie-Tooth disease.

It should be noted that a longitudinal study with neurofilaments is required not only to confirm its ability to reflect the severity of the disease, but also to determine its potential to assess disease progression.

Elīna Kalniņa will defend her doctoral thesis Clinical Variability of Charcot-Marie-Tooth Disease and its Association with Neurofilament and Genetic Type of Disease on 19 May 2023.

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RSU Dissertation Database