Cortical thinning associated with mild cognitive impairment in Parkinson's disease

Segura, Bàrbara; Baggio, Hugo C.; Martí, María Josep; Valldeoriola, Francesc; Compta, Yaroslau; García-Díaz, Anna Isabel; Vendrell, Pere; Bargalló, Núria; Tolosa, Eduardo; Junqué, Carme

doi:10.1002/mds.25982

Cited by 103 publications

(122 citation statements)

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“…(2012) found occipital and inferior parietal hypometabolism in association with more severe cognitive impairment and dementia using fluorodeoxyglucose positron emission tomography34. Finally, in structural MRI studies, PD-MCI patients have been shown to have occipital as well as posterior parietal and temporal cortical thinning3536. Our findings add to this putative relationship between posterior cortical alterations and cognitive impairment in PD.…”

Section: Discussionsupporting

confidence: 52%

Discriminating cognitive status in Parkinson’s disease through functional connectomics and machine learning

Abós

Baggio

Segura

et al. 2017

Sci Rep

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100

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There is growing interest in the potential of neuroimaging to help develop non-invasive biomarkers in neurodegenerative diseases. In this study, connection-wise patterns of functional connectivity were used to distinguish Parkinson’s disease patients according to cognitive status using machine learning. Two independent subject samples were assessed with resting-state fMRI. The first (training) sample comprised 38 healthy controls and 70 Parkinson’s disease patients (27 with mild cognitive impairment). The second (validation) sample included 25 patients (8 with mild cognitive impairment). The Brainnetome atlas was used to reconstruct the functional connectomes. Using a support vector machine trained on features selected through randomized logistic regression with leave-one-out cross-validation, a mean accuracy of 82.6% (p < 0.002) was achieved in separating patients with mild cognitive impairment from those without it in the training sample. The model trained on the whole training sample achieved an accuracy of 80.0% when used to classify the validation sample (p = 0.006). Correlation analyses showed that the connectivity level in the edges most consistently selected as features was associated with memory and executive function performance in the patient group. Our results demonstrate that connection-wise patterns of functional connectivity may be useful for discriminating Parkinson’s disease patients according to the presence of cognitive deficits.

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Section: Discussionsupporting

confidence: 52%

Discriminating cognitive status in Parkinson’s disease through functional connectomics and machine learning

Abós

Baggio

Segura

et al. 2017

Sci Rep

Self Cite

100

View full text Add to dashboard Cite

show abstract

“…Gray matter atrophy in PD has been reported by a number of groups (Hwang et al, 2013; Ibarretxe-Bilbao et al, 2012; Lewis et al, 2016; Pereira et al, 2014; Ramirez-Ruiz et al, 2007; Segura et al, 2014; Song et al, 2011; Tinaz et al, 2011; Zhang et al, 2014), and the current study confirmed these findings in a longitudinal cohort. On the other hand, past research has yielded inconsistent results regarding the extent and nature of white matter involvement in PD.…”

Section: Discussionsupporting

confidence: 90%

Cortical gray and subcortical white matter associations in Parkinson's disease

Sterling

Lewis

et al. 2017

Neurobiology of Aging

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Cortical atrophy has been documented in both Parkinson’s disease (PD) and healthy aging, but its relationship to changes in subcortical white matter is unknown. This was investigated by obtaining T1- and diffusion-weighted images from 76 PD and 70 controls at baseline, 18-, and 36-months, from which cortical volumes and underlying subcortical white matter axial (AD), radial (RD) diffusivities, and fractional anisotropy (FA) were determined. Twelve of 69 cortical subregions had significant group differences, and for these underlying subcortical white matter was explored. At baseline, higher cortical volumes were significantly correlated with lower underlying subcortical white matter AD, RD, and higher FA (Ps ≤0.017) in PD. Longitudinally, higher rates of cortical atrophy in PD were associated with increased rates of change in AD RD, and FA values (Ps ≤ 0.0013) in two subregions explored. The significant gray-white matter associations were not found in controls. Thus, unlike healthy aging, cortical atrophy and subcortical white matter changes may not be independent events in PD.

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“…Cognitive scores in Parkinson's disease patients correlate with dorso-fronto parietal connectivity; inhibited subcortical primary sensory activation; and preserved nigrostriatal pathways in resting-state functional magnetic resonance imaging (fMRI), but not with presynaptic dopaminergic uptake [17]. Atrophy in various cortical regions is associated with neuropsychiatric symptoms [18 & ], as well as MCI in some studies [19,20,21 & ,22 & ,23], though others found no such differences in PD-MCI compared to Parkinson's disease without MCI [24,25]. The expected effect of MCI on the subcortical regions is even less clear, though hippocampal atrophy was found to predict conversion to PD-MCI and to dementia from PD-MCI in a longitudinal study [26].…”

Section: Neuroimaging Mild Cognitive Impairmentmentioning

confidence: 99%

Apathy and noradrenaline

Loued-Khenissi

Preuschoff

2015

Current Opinion in Neurology

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The search for PD-MCI biomarkers has employed an array of neuroimaging techniques, but still yields divergent findings. This may be due in part to MCI's broad definition, encompassing heterogeneous cognitive domains, only some of which are affected in Parkinson's disease. Most domains falling under the MCI umbrella include fronto-dependent executive functions, whereas others, notably learning, rely on the basal ganglia. Given the deterioration of the nigrostriatal dopaminergic system in Parkinson's disease, it has been the prime target of PD-MCI investigation. By testing well defined cognitive deficits in Parkinson's disease, distinct functions can be attributed to specific neural systems, overcoming conflicting results on PD-MCI. Apart from dopamine, other systems such as the neurovascular or noradrenergic systems are affected in Parkinson's disease. These factors may be at the basis of specific facets of PD-MCI for which dopaminergic involvement has not been conclusive. Finally, the impact of both dopaminergic and noradrenergic deficiency on motivational states in Parkinson's disease is examined in light of a plausible link between apathy and cognitive deficits.

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Cortical thinning associated with mild cognitive impairment in Parkinson's disease

Cited by 103 publications

References 46 publications

Discriminating cognitive status in Parkinson’s disease through functional connectomics and machine learning

Discriminating cognitive status in Parkinson’s disease through functional connectomics and machine learning

Cortical gray and subcortical white matter associations in Parkinson's disease

Apathy and noradrenaline

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