Structural Network Efficiency Predicts Conversion to Incident Parkinsonism in Patients With Cerebral Small Vessel Disease

Mengfei Cai; Mina A Jacob; José Marques; David G Norris; Marco Duering; Rianne A J Esselink; Yuhu Zhang; Frank-Erik de Leeuw; Anil M Tuladhar

doi:10.1093/gerona/glad182

Structural Network Efficiency Predicts Conversion to Incident Parkinsonism in Patients With Cerebral Small Vessel Disease

J Gerontol A Biol Sci Med Sci. 2024 Jan 1;79(1):glad182. doi: 10.1093/gerona/glad182.

Authors

Mengfei Cai^{1

2}, Mina A Jacob², José Marques³, David G Norris³, Marco Duering⁴, Rianne A J Esselink², Yuhu Zhang⁵, Frank-Erik de Leeuw², Anil M Tuladhar²

Affiliations

¹ Department of Neurology, Guangdong Cardiovascular Institute, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People's Republic of China.
² Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
³ Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
⁴ Medical Image Analysis Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
⁵ Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People's Republic of China.

Abstract

Background: To investigate whether structural network disconnectivity is associated with parkinsonian signs and their progression, as well as with an increased risk of incident parkinsonism.

Methods: In a prospective cohort (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort study) consisting of 293 participants with small vessel disease (SVD), we assessed parkinsonian signs and incident parkinsonism over an 8-year follow-up. In addition, we reconstructed the white matter network followed by graph-theoretical analyses to compute the network metrics. Conventional magnetic resonance imaging markers for SVD were assessed.

Results: We included 293 patients free of parkinsonism at baseline (2011), with a mean age 68.8 (standard deviation [SD] 8.4) years, and 130 (44.4%) were men. Nineteen participants (6.5%) developed parkinsonism during a median (SD) follow-up time of 8.3 years. Compared with participants without parkinsonism, those with all-cause parkinsonism had higher Unified Parkinson's Disease Rating scale (UPDRS) scores and lower global efficiency at baseline. Baseline global efficiency was associated with UPDRS motor scores in 2011 (β = -0.047, p < .001) and 2015 (β = -0.84, p < .001), as well as with the changes in UPDRS scores during the 4-year follow-up (β = -0.63, p = .004). In addition, at the regional level, we identified an inter-hemispheric disconnected network associated with an increased UPDRS motor score. Besides, lower global efficiency was associated with an increased risk of all-cause and vascular parkinsonism independent of SVD markers.

Conclusions: Our findings suggest that global network efficiency is associated with a gradual decline in motor performance, ultimately leading to incident parkinsonism in the elderly with SVD. Global network efficiency may have the added value to serve as a useful marker to capture changes in motor signs.

Keywords: Motor disturbance; Network efficiency; Parkinsonism; Small vessel disease.

MeSH terms

Aged
Cerebral Small Vessel Diseases* / complications
Cerebral Small Vessel Diseases* / diagnostic imaging
Cohort Studies
Female
Humans
Magnetic Resonance Imaging
Male
Parkinsonian Disorders* / complications
Parkinsonian Disorders* / epidemiology
Prospective Studies

Abstract

MeSH terms

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