Can clinical outputs predict BDNF levels in people with Parkinson's disease?

Objective: To modelling the relationship between Brain-Derived Neurotrophic Factor (BDNF) levels and clinical variables (stages of disease and cognition) in people with Parkinson’s disease (PD). Background: Cognitive dysfunctions affect daily life activities, functional independence and quality of life in people with PD. BDNF levels are considered a marker of neuroplasticity and can contribute to global cognition in people with PD. Method: We applied the Hoehn and Yahr Scale (H&Y) and the Montreal Cognitive Assessment (MoCA) in twenty-nine male and female adults with clinical diagnosis of PD (age: 68 ± 9 years, body mass: 75.54 ±13.5 kg, height 1.67±0.1 m, Unified PD Rating Scale–part III score: 16±6). The ELISA method was used to determine the serum of BDNF levels. Standard statistical methods were used for calculation of the means and standard deviations. Pearson’s correlation coefficient was used to verify the correlations between potential predictors and dependent variables. Additionally, the simple linear regression model was applied to investigate their influence on BDNF levels of people with PD. Statistical Package for Social Sciences (SPSS) software version 20.0 was used to analyse the data. The significance level adopted for both tests was α <0.05. Results: The regression analysis showed that H&Y was able to explain 19% of the variance in global cognition [F (1;27) 6.401; p = 0.018; R2 = 0.192]. The model showed that H&Y and MoCA did not influence the BDNF levels of people with PD [F (1;27) 0.449; p = 0.509; R2 = 0.016]; [F (1;27) 0.074; p = 0.788; R2 = 0.003], respectively. Conclusion: Although H&Y explains 19% of cognition, the clinical outputs did not predict BDNF levels in people with PD.