Biology subjects

Tinaz, S.

Publications and source records attributed to Tinaz, S..

3 recordsLinked to original sources

bioRxiv2026

Denoised MDS-UPDRS Part-III Scores Yield New Patterns of Progression Heterogeneity in Early Stage Parkinson's Disease

Parkinsons Disease (PD) Motor Scores (MDS-UPDRS Part III) are quite noisy. This paper proposes a new methodology for processing these scores by first denoising the scores to enhance the underlying progression signal, and then conducting a high-dimensional analysis which does not sum the scores into a total movement score. The analysis gives novel insights into PD progression heterogeneity: it reveals that the heterogeneity is continuously variable rather than clustered into "subtypes" and that the variability is along two easily understood axes. This analysis also resolves some of the discrepancies in previously reported progression subtypes. Finally, the analysis reveals that patient-specific progression cannot be predicted from baseline using only MDS-UPDRS Part III scores.

bioinformatics↗

bioRxiv2025

Multimodal Neuroimaging Reveals Distinct Characteristics of Levodopa-Induced Dyskinesias in de novo Parkinsons Disease Patients

Levodopa-induced dyskinesia (LID) is a significant treatment complication that affects a substantial proportion of Parkinsons disease (PD) patients. Our understanding of the neural basis of LID remains limited, partly due to the small sample sizes in existing neuroimaging studies. In this study, we utilized structural MRI data from the Parkinsons Progression Markers Initiative (PPMI) database, including de novo PD patients (104 non-dyskinetic for a least 3 years after diagnosis and 120 who developed dyskinesia) and 100 age- and sex-matched healthy controls. Additionally, we analyzed resting-state functional MRI data from a subset of these participants to investigate connectivity differences among the groups. Our analysis revealed no significant baseline volumetric differences between dyskinetic and non-dyskinetic PD patients. However, the thickness of frontal and sensorimotor cortices were significantly greater in dyskinetic patients. In the subcortical regions, vertex-based shape analysis identified localized surface growth in the left caudate and left pallidum, as well as surface morphology changes in the bilateral pallidum in dyskinetics. Resting-state functional connectivity analysis revealed stronger connectivity between the putamen, inferior frontal gyrus, and sensory cortex in dyskinetic PD patients compared to non-dyskinetics. These findings suggest that specific morphological and functional changes in the motor cortical-basal ganglia circuitry of de novo PD patients may predispose them to LID over time. Additionally, the altered functional connectivity patterns reinstate the role of the inferior frontal gyrus in the pathophysiology of dyskinesia and suggest that it might be a suitable target for neuromodulatory interventions, consistent with previous reports.

neuroscience↗

bioRxiv2020

Distinct large-scale networks are associated with motor and nonmotor symptoms in Parkinson's disease

Parkinsons disease (PD) is characterized clinically by various motor and nonmotor symptoms. The underlying neuroanatomical correlates of nonmotor symptoms in PD remain poorly understood. We investigated the differences and commonalities in the neuroanatomical correlates 1) between highly prevalent nonmotor features including fatigue, anxiety, depression, and apathy, and 2) between these nonmotor features and motor severity in nondemented subjects with mild PD (Hoehn & Yahr disease stage 2) using structural and functional magnetic resonance imaging. Compared to matched controls, the PD group showed atrophy in the basal ganglia and superior frontal cortex. Motor severity correlated with cortical thinning in frontotemporal regions, as well as with reduced functional connectivity between the frontostriatal and cerebellar networks. The composite nonmotor symptom severity did not show any correlation with the structural brain data, but correlated with reduced functional connectivity in a large-scale network consisting of frontostriatal, parietotemporal, and cerebellar nodes. The individual components of the nonmotor symptoms also mapped onto specific neural networks. Our study shows that motor and nonmotor features in PD are associated with distinct large-scale networks. The basal ganglia and cerebellum are core regions in all of these networks. The abnormal functional connectivity in the nonmotor network seems to be related to cognitive and emotional dysregulation and may have implications for future cognitive decline in PD.

neuroscience↗