Statistical shape analysis of putamen in early-onset Parkinson’s disease

Sığırlı, Deniz; Ozdemir, Senem Turan; Erer, Sevda; Şahin, İbrahim; Ercan, İlker; Özpar, Rıfat; Örün, Muhammet Okay; Hakyemez, Bahattin

doi:10.1016/j.clineuro.2021.106936

Cited by 10 publications

(8 citation statements)

References 70 publications

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“…We focused on the late-onset PD, because late-onset PD population was larger than early onset PD patients. Late-and early onset PD were separated in many studies (Rango et al, 2021;Sigirli et al, 2021). The patients with low image quality or diagnosed with other diseases, such as Alzheimer's disease, multiple system 10.3389/fnins.2023.1116111 atrophy, dementia with Lewy bodies, during visiting period were excluded from this study.…”

Section: Participantsmentioning

confidence: 99%

Abnormal dynamic functional connectivity changes correlated with non-motor symptoms of Parkinson’s disease

Cao

Tong

et al. 2023

Front. Neurosci.

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BackgroundNon-motor symptoms are common in Parkinson’s disease (PD) patients, decreasing quality of life and having no specific treatments. This research investigates dynamic functional connectivity (FC) changes during PD duration and its correlations with non-motor symptoms.MethodsTwenty PD patients and 19 healthy controls (HC) from PPMI dataset were collected and used in this study. Independent component analysis (ICA) was performed to select significant components from the entire brain. Components were grouped into seven resting-state intrinsic networks. Static and dynamic FC changes during resting-state functional magnetic resonance imaging (fMRI) were calculated based on selected components and resting state networks (RSN).ResultsStatic FC analysis results showed that there was no difference between PD-baseline (PD-BL) and HC group. Network averaged connection between frontoparietal network and sensorimotor network (SMN) of PD-follow up (PD-FU) was lower than PD-BL. Dynamic FC analysis results suggested four distinct states, and each state’s temporal characteristics, such as fractional windows and mean dwell time, were calculated. The state 2 of our study showed positive coupling within and between SMN and visual network, while the state 3 showed hypo-coupling through all RSN. The fractional windows and mean dwell time of PD-FU state 2 (positive coupling state) were statistically lower than PD-BL. Fractional windows and mean dwell time of PD-FU state 3 (hypo-coupling state) were statistically higher than PD-BL. Outcome scales in Parkinson’s disease–autonomic dysfunction scores of PD-FU positively correlated with mean dwell time of state 3 of PD-FU.ConclusionOverall, our finding indicated that PD-FU patients spent more time in hypo-coupling state than PD-BL. The increase of hypo-coupling state and decrease of positive coupling state might correlate with the worsening of non-motor symptoms in PD patients. Dynamic FC analysis of resting-state fMRI can be used as monitoring tool for PD progression.

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Section: Participantsmentioning

confidence: 99%

Abnormal dynamic functional connectivity changes correlated with non-motor symptoms of Parkinson’s disease

Cao

Tong

et al. 2023

Front. Neurosci.

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“…Rab3A has been indicated as one of physiological substrates of leucine-rich repeat kinase 2 (LRRK2) whose increased activity is related to PD pathogenesis [57]. In light of the functions ascribed to Rab3A, the high expression of Rab3A in pig PU adds molecular evidence in support of the potential role of this brain area in PD pathogenesis as prompted by different approaches such as shape analysis [58], and it is worth noting that Rab3A expression was also elevated in CLA with a value significantly higher than in IN, suggesting a possible common role of PU and CLA in neurological disorders. Exclusive expression differences were observed for SIRT2, PDIA3, TKT, and GOT2 in CLA vs PU.…”

Section: Discussionmentioning

confidence: 99%

Proteomic Profiling Reveals Specific Molecular Hallmarks of the Pig Claustrum

et al. 2023

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The present study, employing a comparative proteomic approach, analyzes the protein profile of pig claustrum (CLA), putamen (PU), and insula (IN). Pig brain is an interesting model whose key translational features are its similarities with cortical and subcortical structures of human brain. A greater difference in protein spot expression was observed in CLA vs PU as compared to CLA vs IN. The deregulated proteins identified in CLA resulted to be deeply implicated in neurodegenerative (i.e., sirtuin 2, protein disulfide-isomerase 3, transketolase) and psychiatric (i.e., copine 3 and myelin basic protein) disorders in humans. Metascape analysis of differentially expressed proteins in CLA vs PU comparison suggested activation of the α-synuclein pathway and L1 recycling pathway corroborating the involvement of these anatomical structures in neurodegenerative diseases. The expression of calcium/calmodulin-dependent protein kinase and dihydropyrimidinase like 2, which are linked to these pathways, was validated using western blot analysis. Moreover, the protein data set of CLA vs PU comparison was analyzed by Ingenuity Pathways Analysis to obtain a prediction of most significant canonical pathways, upstream regulators, human diseases, and biological functions. Interestingly, inhibition of presenilin 1 (PSEN1) upstream regulator and activation of endocannabinoid neuronal synapse pathway were observed. In conclusion, this is the first study presenting an extensive proteomic analysis of pig CLA in comparison with adjacent areas, IN and PUT. These results reinforce the common origin of CLA and IN and suggest an interesting involvement of CLA in endocannabinoid circuitry, neurodegenerative, and psychiatric disorders in humans.

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“…Studies that performed further surface morphometric analyses under automated shape analyses showed: (1) A regional contraction of the posterolateral and ventromedial putamen bilaterally in patients with PD[ 14 ]; (2) areas of local atrophy in the lateral and medial posterior parts of the bilateral putamen; (3) atrophy locally on the medial surface of the left caudate nucleus[ 21 ]; and (4) a reduction in the volume and an inward displacement of the surface of the caudal motor striatum[ 22 ]. Studies using other machine learning methods have also found local atrophy in the caudate and putamen nuclei, including the caudal portion of the putamen or the middle-posterior putamen and the head of the caudate[ 13 , 23 ]. A study attempted to distinguish different stages of PD based solely on the shape analysis of the bilateral caudate nucleus and putamen through an automated process, with balanced accuracies in the range of 59%-85%[ 24 ].…”

Section: Resultsmentioning

confidence: 99%

“…Specifically, volume atrophy of the left caudate nucleus or right putamen was found to be more pronounced in the patient cohort[ 11 , 23 ], which may be due to disease lateralization. Previous studies have shown that the decrease in dopamine capacity in the striatum is more pronounced in the contralateral hemisphere on the side with more severe clinical symptoms of PD[ 36 ].…”

Section: Resultsmentioning

confidence: 99%

“…Local deformation of the posterior side of the putamen has been reported in several articles. According to the literature, the posterior putamen is directly related to the sensorimotor cortex and is preferentially affected; dopamine depletion is mainly located in this region of the basal ganglia[ 10 , 23 , 37 , 38 ]. Therefore, we can also infer that the morphological changes in PD can be detected using MRI.…”

Section: Resultsmentioning

confidence: 99%

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Morphological changes in Parkinson's disease based on magnetic resonance imaging: A mini-review of subcortical structures segmentation and shape analysis

Deng¹,

Zhang²,

Liu³

et al. 2022

World J Psychiatry

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Parkinson's disease (PD) is a neurodegenerative disorder caused by the loss of dopaminergic neurons in the substantia nigra, resulting in clinical symptoms, including bradykinesia, resting tremor, rigidity, and postural instability. The pathophysiological changes in PD are inextricably linked to the subcortical structures. Shape analysis is a method for quantifying the volume or surface morphology of structures using magnetic resonance imaging. In this review, we discuss the recent advances in morphological analysis techniques for studying the subcortical structures in PD in vivo . This approach includes available pipelines for volume and shape analysis, focusing on the morphological features of volume and surface area.

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Statistical shape analysis of putamen in early-onset Parkinson’s disease

Cited by 10 publications

References 70 publications

Abnormal dynamic functional connectivity changes correlated with non-motor symptoms of Parkinson’s disease

Abnormal dynamic functional connectivity changes correlated with non-motor symptoms of Parkinson’s disease

Proteomic Profiling Reveals Specific Molecular Hallmarks of the Pig Claustrum

Morphological changes in Parkinson's disease based on magnetic resonance imaging: A mini-review of subcortical structures segmentation and shape analysis

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