Motor progression phenotypes in early-stage Parkinson's Disease: A clinical prediction model and the role of glymphatic system imaging biomarkers.

BACKGROUND: Substantial heterogeneity of motor symptoms in Parkinson's disease (PD) poses a challenge to disease prediction. OBJECTIVES: The aim of this study was to construct a nomogram model that can distinguish different longitudinal trajectories of motor symptom changes in early-stage PD patients. METHODS: Data on 90 patients with 5-years of follow-up were collected from the Parkinson's Progression Marker Initiative (PPMI) cohort. We used a latent class mixed modeling (LCMM) to identify distinct progression patterns of motor symptoms, and backward stepwise logistic regression with baseline information was conducted to identify the potential predictors for motor trajectory and to develop a nomogram. The performance of the nomogram model was then evaluated using the optimism-corrected C-index for internal validation, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve for discrimination, the calibration curve for predictive accuracy, and decision curve analysis (DCA) for its clinical value. RESULTS: We identified two trajectories for motor progression patterns. The first, Class 1 (Motor deteriorated group), was characterized by sustained, continuously worsening motor symptoms, and the second, Class 2 (Motor stable group), had stable motor symptoms throughout the follow-up period. The best combination of 7 baseline variables was identified and assembled into the nomogram: Scopa-AUT [odds ratio (OR), 1.11; p = 0.091], Letter number sequencing (LNS) (OR, 0.76; p = 0.068), the asymmetry index of putamen (OR, 0.95; p = 0.034), mean caudate uptake (OR, 0.14; p = 0.086), CSF pTau/α-synuclein (OR, 0.00; p = 0.011), CSF tTau/Aß (OR, 25434806; p = 0.025), and the index for diffusion tensor image analysis along the perivascular space (ALPS-index) (OR, 0.02; p = 0.030). The nomogram achieved good discrimination, with an original AUC of 0.901 (95% CI, 0.813-0.989), and the bias-corrected concordance index (C-index) with 1,000 bootstraps was 0.834. The calibration curve and DCA also suggested both the high accuracy and clinical usefulness of the nomogram, respectively. CONCLUSIONS: This study proposes an effective nomogram to predict different motor progression patterns in early-stage PD. Furthermore, the imaging biomarker indicating glymphatic function could be an independent predictive factor for PD motor progression.

Neuronavigated repetitive transcranial magnetic stimulation improves depression, anxiety and motor symptoms in Parkinson's disease.

Background: Repetitive transcranial magnetic stimulation (rTMS) is a potential treatment option for Parkinson's disease patients with depression (DPD), but conflicting results in previous studies have questioned its efficacy. Method: To investigate the safety and efficacy of neuronavigated high-frequency rTMS at the left DLPFC in DPD patients, we conducted a randomized, double-blind, sham-controlled study (NCT04707378). Sixty patients were randomly assigned to either a sham or active stimulation group and received rTMS for ten consecutive days. The primary outcome was HAMD, while secondary outcomes included HAMA, MMSE, MoCA and MDS-UPDRS-III. Assessments were performed at baseline, immediately after treatment, 2 weeks, and 4 weeks post-treatment. Results: The GEE analysis showed that the active stimulation group had significant improvements in depression, anxiety, and motor symptoms at various time points. Specifically, there were significant time-by-group interaction effects in depression immediately after treatment (ß, -4.34 [95% CI, -6.90 to -1.74; P = 0.001]), at 2 weeks post-treatment (ß, -3.66 [95% CI, -6.43 to -0.90; P = 0.010]), and at 4 weeks post-treatment (ß, -4.94 [95% CI, -7.60 to -2.29; P < 0.001]). Similarly, there were significant time-by-group interaction effects in anxiety at 4 weeks post-treatment (ß, -2.65 [95% CI, -4.96 to -0.34; P = 0.024]) and in motor symptoms immediately after treatment (ß, -5.72 [95% CI, -9.10 to -2.34; P = 0.001] and at 4 weeks post-treatment (ß, -5.43 [95% CI, -10.24 to -0.61; P = 0.027]). Conclusion: The study suggested that neuronavigated high-frequency rTMS at left DLPFC is effective for depression, anxiety, and motor symptoms in PD patients.

Gut Microbiota Altered in Mild Cognitive Impairment Compared With Normal Cognition in Sporadic Parkinson's Disease.

Background and Aim: Gut bacteria play an important role in the pathogenesis of Parkinson's disease (PD). However, the alteration of fecal microbiota in PD with cognitive impairment remains unexplored. This study aimed to explore whether the gut microbiota of patients with PD having mild cognitive impairment (PD-MCI) were different from those with PD having normal cognition (PD-NC) and from healthy controls (HC). Also, the study probed the association between altered gut microbiota and cognitive ability in patients with PD. Methods: The fecal bacteria composition and short-chain fatty acids of 13 patients with PD-MCI, 14 patients with PD-NC, and 13 healthy spouses were analyzed using 16S ribosomal RNA sequencing and gas chromatography-mass spectrometry. Results: Compared with HC, the fecal microbial diversities increased in patients with PD-MCI and PD-NC. After adjusting the influence of age, sex, body mass index, education, and constipation using the statistical method, the relative abundances of two families (Rikenellaceae and Ruminococcaceae) and four genera (Alistipes, Barnesiella, Butyricimonas, and Odoribacter) were found to be higher in the feces of the PD-MCI group compared with the other two groups. Moreover, the abundance of genus Blautia and Ruminococcus decreased obviously in the PD-MCI group compared with the PD-NC group. Further, the abundance of genera Butyricimonas, Barnesiella, Alistipes, Odoribacter, and Ruminococcus negatively correlated with cognition ability. Conclusion: Compared with HC and patients with PD-NC, the gut microbiota of patients with PD-MCI was significantly altered, particularly manifesting in enriched genera from Porphyromonadaceae family and decreased the abundance of genera Blautia and Ruminococcus.