LRRK2 (Leucine-Rich Repeat Kinase 2) Parkinson's Disease Fingerprint

Movement Disorders Society- Unified PD Rating Scale (MDS-UPDRS). The scoring basis is 0 to 4. The total score across all parts ranges from 0 (no disability) to 260 (total disability). The higher the score, the more advanced or severe the symptoms are.

The Hoehn and Yahr (H&Y) scale. Stage 0: No signs of disease. Stage 1: Unilateral (one-sided) disease involvement only, with minimal or no functional impairment.

Stage 1.5: Unilateral plus axial (neck/torso) involvement. Stage 2: Bilateral or midline involvement, without impairment of balance. Stage 2.5: Mild bilateral disease, with recovery on the clinical "pull test" (balance reflex assessment).

Stage 3: Mild to moderate bilateral disease; some postural instability, but the patient remains physically independent.

Stage 4: Severe disability; however, the patient is still able to walk or stand unassisted.

Stage 5: Wheelchair-bound or bedridden unless aided.

Unified dyskinesia rating scale (UDysRS). Scoring uses a 0 to 4 Likert-type scale, where higher scores indicate greater dyskinesia severity and impairment.

Non-Motor symptoms scale (NMSS). Each of the 30 items is scored by multiplying its severity (0-3) by its frequency (1-4), yielding a possible subscore from 0-12 per item and a total score ranging from 0 to 360.

Severity: 0 = None, 1 = Mild: symptoms present but causes little distress or disturbance to patient; 2 = Moderate: some distress or disturbance to patient; 3 = Severe: major source of distress or disturbance to patient.

Frequency: 1 = Rarely (<1/wk); 2 = Often (1/wk); 3 = Frequent (several times per week); 4 = Very Frequent (daily or all the time).

Montreal Cognitive Assessment (MoCA). Total Score: 30 points possible. Normal Result: A score of 26 or higher is typically considered normal.

Mini Mental status evaluation (MMSE). While the scoring is out of 30 points, results are often categorized to gauge severity:

25-30: Normal cognitive function. 21-24: Mild cognitive impairment. 10-20: Moderate cognitive impairment. Below 10: Severe cognitive impairment.

Questionnaire for impulsive-compulsive disorders (QUIP). A rating scale measuring symptom severity. It evaluates 4 primary impulse control disorders (gambling, sexual, buying, eating) and related behaviors, scoring them from 0 to 16 based on thoughts, urges, and difficulty to control.

Beck depression inventory (BDI). Each statement is assigned a value from 0 to 3. The scores for all 21 questions are added together to produce a total score between 0 and 63.

Total score:

0 to 13: Minimal depression 14 to 19: Mild depression 20 to 28: Moderate depression 29 to 63: Severe depression

Beck Anxiety Inventory (BAI). Scoring basis: ranging from 0 (not at all) to 3 (severely).

Total score:

0-7: Minimal anxiety 8-15: Mild anxiety 16-25: Moderate anxiety 26-63: Severe anxiety

Molecular markers assessment: A panel of pro- and anti-inflammatory mediators will be analysed (IL1-b, TNFa, IFNg, IL4, IL5, IL6, IL17, IL10) along with Neurofilament light chain. The unit of measure is pg/mL.

IDENTIFY relevant data features (months 12-36). This task seeks to map large-scale brain dynamics (EEG-derived metrics) to symptoms-related changes in idiopathic PD (Parkinson's Disease) vs LRRK2-PD, before and after dopaminergic therapy. The success of task one will be evaluated on the predictive power of the EEG-derived metrics to distinguish ON/OFF, LRRK2/Idiopathic patients and to predict clinical symptoms.

PREDICT such changes using patient-specific in silico models (months 12-36). This task aims to develop a mechanistic model that simulates the effects of changes in Protocol NEU-PD V.1.0 of 05th May 2026 Pag. 7 | 10 activities in the SPNs (i.e. firing rate, spontaneous excitability - glutamatergic activity) on the whole-brain dynamics at the individual level. A brain model consists of a set of equations that encapsulate pathophysiological knowledge and patient-specific features. Solving the model generates patient-specific synthetic brain data. In these models the brain is parceled in a set of regions based on anatomo-functional atlases. Each node is informed with specific features that determine the local activities. In-silico simulations allow to infer how large-scale dynamics emerge from the interaction of local properties. The success of this task will be measured by the model's ability to reproduce conditionspecific (LRRK2/PD) EEG signal features.