Анналы клинической и экспериментальной неврологии (Sep 2023)
Biochemical markers of neurodegeneration in patients with cerebral small vessel disease and Alzheimer's disease
Abstract
Introduction. Cerebral small vessel disease (CSVD) as well as the Alzheimer's disease (AD) and their comorbidities are the most common causes of cognitive impairments (CIs). Objective: to evaluate the predictive power of the biochemical neurodegeneration markers in patients with CSVD and AD. Materials and methods. We assessed the following neurodegeneration markers in 68 patients with CSVD (61.0 8.6 years; 60.3% males), 17 patients with AD (65.2 8.3 years; 35.3% males), and 26 healthy volunteers (59.9 6.7 years; 38.5% males): neuron-specific enolase (NSE), glial fibrillary acid protein (GFAP), neurofilament light polypeptide (NEFL) in blood (for all patients) and in cerebrospinal fluid (CSF; in patients with CSVD and AD). We assessed the predictive power of those markers with ROC analysis. Results. As compared to the control group, serum GFAP in patients with CSVD showed its predictive power at 0.155 ng/ml (sensitivity 74%; specificity 70%). Serum NEFL 0.0185 ng/ml (sensitivity 82%; specificity 96%) and NSE 4.95 g/ml (sensitivity 77%; specificity 71%) showed their predictive power in patients with AD. CSF GFAP 1.03 ng/ml (sensitivity 84%; specificity 88%), CSF NSE 19.10 g/ml (sensitivity 88%; specificity 91%), serum NEFL 0.021 ng/ml (sensitivity 71%; specificity 76%), serum NSE /CSF NSE ratio 0.273 ng/ml (sensitivity 87%; specificity 88%) help differentiate CSVD from AD. Conclusions. We found that serum GFAP can be a useful diagnostic marker in patients with CSVD, while serum NEFL and serum NSE can help identify the AD. In addition, CSF GFAP and CSF NSE as well as serum NEFL and serum NSE/CSF NSE can help differentiate CSVD from AD. We can use those markers in clinical and research practice to identify the vascular and neurodegenerative causes of CIs and their comorbidities, which is of a great importance in developing specific treatment and predicting the course of the disease.
Keywords