Dopaminergic imaging in degenerative parkinsonisms, an established clinical diagnostic tool

Nicastro, Nicolas; Nencha, Umberto; Burkhard, Pierre; Garibotto, Valentina

doi:10.1111/jnc.15561

Cited by 15 publications

(15 citation statements)

References 243 publications

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“…), or postsynaptic terminals [ 11 C-raclopride, 123 I-iodobenzamide (IBZM), etc.] ( 92 ). Dopaminergic deficits were evaluated by the techniques mentioned above, especially in patients with familial FTLD with Parkinsonism.…”

Section: Discussionmentioning

confidence: 99%

Molecular imaging biomarkers in familial frontotemporal lobar degeneration: Progress and prospects

et al. 2022

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Familial frontotemporal lobar degeneration (FTLD) is a pathologically heterogeneous group of neurodegenerative diseases with diverse genotypes and clinical phenotypes. Three major mutations were reported in patients with familial FTLD, namely, progranulin (GRN), microtubule-associated protein tau (MAPT), and the chromosome 9 open reading frame 72 (C9orf72) repeat expansion, which could cause neurodegenerative pathological changes years before symptom onset. Noninvasive quantitative molecular imaging with PET or single-photon emission CT (SPECT) allows for selective visualization of the molecular targets in vivo to investigate brain metabolism, perfusion, neuroinflammation, and pathophysiological changes. There was increasing evidence that several molecular imaging biomarkers tend to serve as biomarkers to reveal the early brain abnormalities in familial FTLD. Tau-PET with 18F-flortaucipir and 11C-PBB3 demonstrated the elevated tau position in patients with FTLD and also showed the ability to differentiate patterns among the different subtypes of the mutations in familial FTLD. Furthermore, dopamine transporter imaging with the 11C-DOPA and 11C-CFT in PET and the 123I-FP-CIT in SPECT revealed the loss of dopaminergic neurons in the asymptomatic and symptomatic patients of familial FTLD. In addition, PET imaging with the 11C-MP4A has demonstrated reduced acetylcholinesterase (AChE) activity in patients with FTLD, while PET with the 11C-DAA1106 and 11C-PK11195 revealed an increased level of microglial activation associated with neuroinflammation even before the onset of symptoms in familial FTLD. 18F-fluorodeoxyglucose (FDG)-PET indicated hypometabolism in FTLD with different mutations preceded the atrophy on MRI. Identifying molecular imaging biomarkers for familial FTLD is important for the in-vivo assessment of underlying pathophysiological changes with disease progression and future disease-modifying therapy. We review the recent progress of molecular imaging in familial FTLD with focused on the possible implication of these techniques and their prospects in specific mutation types.

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Section: Discussionmentioning

confidence: 99%

Molecular imaging biomarkers in familial frontotemporal lobar degeneration: Progress and prospects

et al. 2022

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“…Unique to DLB and other Lewy body diseases, PET and SPECT measures of dopaminergic neurotransmission represent excellent biomarkers for differential diagnosis 90 . Specifically, SPECT and PET studies targeting the dopamine transporter (DAT) with [ 123 I]FP-CIT and dopamine receptors (ie, D2 receptors) have shown reduced tracer binding in the striatum and cortex in DLB and PDD, which can differentiate DLB from AD ( figure 9-5c ).…”

Section: Parkinson Disease Dementia and Dementia With Lewy Bodiesmentioning

confidence: 99%

Neuroimaging in Dementia

Risacher¹,

Apostolova²

2023

CONTINUUM: Lifelong Learning in Neurology

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OBJECTIVE: Neurodegenerative diseases are significant health concerns with regard to morbidity and social and economic hardship around the world. This review describes the state of the field of neuroimaging measures as biomarkers for detection and diagnosis of both slowly progressing and rapidly progressing neurodegenerative diseases, specifically Alzheimer disease, vascular cognitive impairment, dementia with Lewy bodies or Parkinson disease dementia, frontotemporal lobar degeneration spectrum disorders, and prion-related diseases. It briefly discusses findings in these diseases in studies using MRI and metabolic and molecular-based imaging (eg, positron emission tomography [PET] and single-photon emission computerized tomography [SPECT]).LATEST DEVELOPMENTS: Neuroimaging studies with MRI and PET have demonstrated differential patterns of brain atrophy and hypometabolism in different neurodegenerative disorders, which can be useful in differential diagnoses. Advanced MRI sequences, such as diffusion-based imaging, and functional MRI (fMRI) provide important information about underlying biological changes in dementia and new directions for development of novel measures for future clinical use. Finally, advancements in molecular imaging allow clinicians and researchers to visualize dementia-related proteinopathies and neurotransmitter levels.ESSENTIAL POINTS: Diagnosis of neurodegenerative diseases is primarily based on symptomatology, although the development of in vivo neuroimaging and fluid biomarkers is changing the scope of clinical diagnosis, as well as the research into these devastating diseases. This article will help inform the reader about the current state of neuroimaging in neurodegenerative diseases, as well as how these tools might be used for differential diagnoses.

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“…Its clinical symptoms include static tremors, muscle tension, and loss of smell ( Bostantjopoulou et al, 2013 ). Although Positron Emission Computed Tomography (PET) imaging of dopamine transporter is used in the diagnosis of PD, it is expensive and inconvenient and therefore not suitable for some medical centers ( Nicastro et al, 2021 ). Currently, PD is mainly diagnosed based on physical examination and clinical symptoms, and there are no affordable, effective, and less invasive examination methods ( Farotti et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

A computational approach based on weighted gene co-expression network analysis for biomarkers analysis of Parkinson’s disease and construction of diagnostic model

Hu²,

Gao³

et al. 2023

Front. Comput. Neurosci.

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BackgroundParkinson’s disease (PD) is a common age-related chronic neurodegenerative disease. There is currently no affordable, effective, and less invasive test for PD diagnosis. Metabolite profiling in blood and blood-based gene transcripts is thought to be an ideal method for diagnosing PD.AimIn this study, the objective is to identify the potential diagnostic biomarkers of PD by analyzing microarray gene expression data of samples from PD patients.MethodsA computational approach, namely, Weighted Gene Co-expression Network Analysis (WGCNA) was used to construct co-expression gene networks and identify the key modules that were highly correlated with PD from the GSE99039 dataset. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was performed to identify the hub genes in the key modules with strong association with PD. The selected hub genes were then used to construct a diagnostic model based on logistic regression analysis, and the Receiver Operating Characteristic (ROC) curves were used to evaluate the efficacy of the model using the GSE99039 dataset. Finally, Reverse Transcription-Polymerase Chain Reaction (RT-PCR) was used to validate the hub genes.ResultsWGCNA identified two key modules associated with inflammation and immune response. Seven hub genes, LILRB1, LSP1, SIPA1, SLC15A3, MBOAT7, RNF24, and TLE3 were identified from the two modules and used to construct diagnostic models. ROC analysis showed that the diagnostic model had a good diagnostic performance for PD in the training and testing datasets. Results of the RT-PCR experiments showed that there were significant differences in the mRNA expression of LILRB1, LSP1, and MBOAT7 among the seven hub genes.ConclusionThe 7-gene panel (LILRB1, LSP1, SIPA1, SLC15A3, MBOAT7, RNF24, and TLE3) will serve as a potential diagnostic signature for PD.

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Dopaminergic imaging in degenerative parkinsonisms, an established clinical diagnostic tool

Cited by 15 publications

References 243 publications

Molecular imaging biomarkers in familial frontotemporal lobar degeneration: Progress and prospects

Molecular imaging biomarkers in familial frontotemporal lobar degeneration: Progress and prospects

Neuroimaging in Dementia

A computational approach based on weighted gene co-expression network analysis for biomarkers analysis of Parkinson’s disease and construction of diagnostic model

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