Identifying a whole‐brain connectome‐based model in drug‐naïve Parkinson's disease for predicting motor impairment

Abstract Background The functional alternation of distinct brain networks contribute to motor impairment in Parkinson’s disease (PD) remains unclear. Identifying a whole-brain connectome-based predictive model (CPM) in drug-naïve patients and verifying its predictability among drug-managed patients would be helpful to detect generalizable brain-behavior association and reflect intrinsic functional underpinning of motor impairment. Methods Resting-state functional data of 47 drug-naïve patients were enrolled to construct a predictive model by using the CPM approach, which was subsequently validated in 115 drug-managed patients. The severity of motor impairment was assessed by calculating Unified Parkinson’s Disease Rating Scale part III (UPDRS III) scores. Predictive performance was evaluated with the correlation coefficient(rtrue) and the mean squared error (MSE) between observed and predicted scores. Results A CPM for predicting individual motor impairment in drug-naïve PD was identified with significant performance (rtrue=0.845, p < 0.001, MSE = 137.57). Two connection patterns were recognized according to the correlation coefficients between the connections’ strength and motor impairment severity. The negative motor-impairment-related network contained more within-network connections in the motor, visual-related, and default mode networks, while the positive motor-impairment-related network was constructed mostly with between-network connections coupled motor-visual, motor-limbic, and motor-basal ganglia networks. The predictability of constructed model was further confirmed in drug-managed patients (r = 0.209, p = 0.025, MSE = 182.96), suggesting generalizability in PD patients with lasting dopaminergic medication influence. Conclusions This study identified a whole-brain connectome-based model that could predict the severity of motor impairment for PD. The connection patterns generated from the model reflected that functional segregation of motor, visual-related, and default mode networks play an important role in PD motor impairment, and higher connections coupling motor and non-motor regions might demonstrate a compensatory mechanism to overcome motor impairment.

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Identifying a Whole-brain Connectome-based Model in Drug-naïve Parkinson’s Disease for Predicting Motor Impairment

10.21203/rs.3.rs-779169/v2 ◽

2021 ◽

Author(s):

Haoting Wu ◽

Cheng Zhou ◽

Tao Guo ◽

Jingjing Wu ◽

Xueqin Bai ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Predictive Model ◽

Rating Scale ◽

Motor Impairment ◽

Predictive Performance ◽

Whole Brain ◽

Brain Connectome ◽

Network Connections ◽

Drug Naïve

Abstract Identifying a whole-brain connectome-based predictive model in drug-naïve patients with Parkinson’s disease and verifying its predictions on drug-managed patients would be useful in determining the intrinsic functional underpinnings of motor impairment and establishing general brain-behavior associations. In this study, we constructed a predictive model from the resting-state functional data of 47 drug-naïve patients by using a connectome-based approach. This model was subsequently validated in 115 drug-managed patients. The severity of motor impairment was assessed by calculating Uniﬁed Parkinson’s Disease Rating Scale Part III scores. The predictive performance of model was evaluated using the correlation coefficient (rtrue) between predicted and observed scores. As a result, a connectome-based model for predicting individual motor impairment in drug-naïve patients was identified with significant performance (rtrue = 0.845, p < 0.001, ppermu = 0.002). Two patterns of connection were identified according to correlations between connection strength and the severity of motor impairment. The negative motor-impairment-related network contained more within-network connections in the motor, visual-related, and default mode networks, whereas the positive motor-impairment-related network was constructed mostly with between-network connections coupling the motor-visual, motor-limbic, and motor-basal ganglia networks. Finally, this predictive model constructed around drug-naïve patients was confirmed with significant predictive efficacy on drug-managed patients (r = 0.209, p = 0.025), suggesting a generalizability in Parkinson’s disease patients under long-term drug influence. In conclusion, this study identified a whole-brain connectome-based model that could predict the severity of motor impairment in Parkinson’s patients and furthers our understanding of the functional underpinnings of the disease.

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Sex-specific whole-brain network topologic organization in drug naïve Parkinson's disease patients

Journal of the Neurological Sciences ◽

10.1016/j.jns.2021.119459 ◽

2021 ◽

Vol 429 ◽

pp. 119459

Author(s):

Sara Satolli ◽

Federica Agosta ◽

Rosa De Micco ◽

Silvia Basaia ◽

Mattia Siciliano ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Brain Network ◽

Whole Brain ◽

Drug Naïve

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4302 Decreased structural basal ganglia motor loop connections in Vascular Parkinsonism compared to Parkinson’s disease and healthy aging

Journal of Clinical and Translational Science ◽

10.1017/cts.2020.295 ◽

2020 ◽

Vol 4 (s1) ◽

pp. 94-94

Author(s):

Christine Cooper ◽

Federico Rodriguez-Porcel ◽

Travis Turner ◽

Gonzalo Revuelta ◽

Jens Jensen ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Basal Ganglia ◽

Healthy Aging ◽

Lower Body ◽

Vascular Parkinsonism ◽

Whole Brain ◽

Brain Connectome ◽

Clinical Scores ◽

Motor Loop

OBJECTIVES/GOALS: This study uses diffusion kurtosis imaging (DKI) to investigate the structural profiles of basal ganglia (BG) motor circuitry in Vascular Parkinsonism (VP), Parkinson’s disease (PD), and healthy aging controls (HC). VP is a clinical diagnosis of lower body predominant parkinsonism without significant benefit from levodopa. VP is distinct from PD, yet the concept of VP remains debated due to the inability of prior studies to identify specific causative changes. One reason for this may be limitations in measuring intricate BG connectivity in vivo. Given the predominant lower body parkinsonism symptoms in VP, we hypothesized that VP would be associated with decreased connectivity specifically within the BG motor loop. METHODS/STUDY POPULATION: We obtained DKI brain imaging in subjects with VP (N = 7), PD (N = 21), and HCs (N = 58), the latter of which had cardiovascular risk factors but no neurological symptoms. The VP and PD groups were evaluated by a parkinsonism-focused motor exam and brief cognitive testing. We compared BG motor loop connectivity between groups and investigated for correlation between connectivity and clinical scores. To account for differences in fiber counts due to the different imaging scanners and protocols between cohorts, we used a BG motor loop proportion, which was the ratio of the BG motor loop fiber count over a control loop, the visual processing pathway. We used Kruskal-Wallis rank sum test with post-hoc Dunn tests to assess imaging findings between subject groups, and Pearson’s correlation to look for correlation between clinical scores and fiber counts. RESULTS/ANTICIPATED RESULTS: The whole brain connectome showed the fewest number of fibers in VP, followed by PD, and then HC (p<0.0001). The BG motor loop proportion fiber count of the BG motor loop was lower in the VP group, compared to the PD and HC cohorts (p = 0.031). In the VP group, the whole brain connectome fiber count correlated with a gait and balance subscore of the Movement Disorders Society - Unified Parkinson Disease Rating Scale (R = −0.87, p = 0.01). DISCUSSION/SIGNIFICANCE OF IMPACT: This study indicates that VP is associated with decreased structural connectivity, with a disproportionate degree of loss in the BG motor circuitry. While the etiology for this susceptibility to injury and preferential damage to BG remains to be defined, these findings can provide an important starting point for a biological understanding of VP, and a potential future marker for diagnosis and tracking disease progression.

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Faculty Opinions recommendation of Decreased binding of the D3 dopamine receptor-preferring ligand [11C]-(+)-PHNO in drug-naive Parkinson's disease.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1148194.605332 ◽

2009 ◽

Author(s):

David Brooks ◽

Nicola Pavese

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Dopamine Receptor ◽

Drug Naïve

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Altered intrinsic brain functional connectivity in drug-naïve Parkinson’s disease patients with LRRK2 mutations

Neuroscience Letters ◽

10.1016/j.neulet.2018.03.038 ◽

2018 ◽

Vol 675 ◽

pp. 145-151 ◽

Cited By ~ 5

Author(s):

Yanbing Hou ◽

Chunyan Luo ◽

Jing Yang ◽

Ruwei Ou ◽

Wei Song ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Functional Connectivity ◽

Drug Naïve ◽

Brain Functional Connectivity

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Parkinson’s Disease Motor Symptom Progression Slowed with Multisensory Dance Learning over 3-Years: A Preliminary Longitudinal Investigation

Brain Sciences ◽

10.3390/brainsci11070895 ◽

2021 ◽

Vol 11 (7) ◽

pp. 895

Author(s):

Karolina A. Bearss ◽

Joseph F. X. DeSouza

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Daily Living ◽

Rating Scale ◽

Motor Impairment ◽

Motor Dysfunction ◽

Motor Symptom ◽

Significant Group ◽

Rate Of Decline ◽

Symptom Progression

Parkinson’s disease (PD) is a neurodegenerative disease that has a fast progression of motor dysfunction within the first 5 years of diagnosis, showing an annual motor rate of decline of the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) between 5.2 and 8.9 points. We aimed to determine both motor and non-motor PD symptom progression while participating in dance classes once per week over a period of three years. Longitudinal data was assessed for a total of 32 people with PD using MDS-UPDRS scores. Daily motor rate of decline was zero (slope = 0.000146) in PD-Dancers, indicating no motor impairment, whereas the PD-Reference group showed the expected motor decline across three years (p < 0.01). Similarly, non-motor aspects of daily living, motor experiences of daily living, and motor complications showed no significant decline. A significant group (PD-Dancers and PD-Reference) by days interaction showed that PD who train once per week have less motor impairment (M = 18.75) than PD-References who do not train (M = 24.61) over time (p < 0.05). Training is effective at slowing both motor and non-motor PD symptoms over three years as shown in decreased scores of the MDS-UPDRS.

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