[Identification of people at the latent stage of Parkinson's disease (the PARKINLAR study): first results and an optimization of the algorithm].

AIM: To work out an optimal algorithm to identify people at the latent stage of neurodegenerative process of «parkinsonian» type in the Russian population.

MATERIAL AND

METHODS

Authors launched a two-step study aimed at identifying people at the latent stage of Parkinson's disease (PD) in the Russian population - the PARKINLAR (PARKINsonism, LAtent stage, Russia). As the first step, we formed a group of «primary risk» by the identification in neurologically healthy people of at least one of the following confirmed PD risk factors: a) the substantia nigra hyperechogenicity (ultrasound screening was performed in 193 people); b) mutations in «parkinsonian» genes (genetic screening was performed in 29 relatives of PD patients from families with LRRK2, PARK2 and GBA mutations). Thereby, 37 people comprised the «primary risk» group, of whom 23 agreed to continue further examination (44±10.2 years). A matched group of people without the aforementioned primary biomarkers of PD served as control. As the second step, we undertook in the prescreened groups a complex of investigations assessing the presence of secondary («minor») biomarkers of PD: Sniffin' Sticks olfactory testing; color visual evoked potentials; analysis of goal-directed eye-head-hand movements with the use of a special neuro-cybernetic system; assessment of motor and non-motor symptoms with the use of UPDRS and NMSS scales.

RESULTS

When comparing the «primary risk» group with controls, maximal differences in the occurrence of symptoms were seen for goal-directed eye movements (43.5% vs. 20.0%) and color vision (39.1% vs. 26.7%). Among these individuals, we found two people with 4 secondary biomarkers and one with 3, and no such observations in controls. People with the combination of a primary biomarker with several secondary biomarkers of PD comprised a group of «high risk» in our study.

CONCLUSION

Optimization of this algorithm of population screening of people predisposed to the development of PD may be done by expanding the spectrum of biomarkers and assessing their validity in a long-term prospective observational study.