OBJECTIVE: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy bodies (DLB). METHODS: In this multicenter study of the International RBD study group, 173 patients (mean age 70.5 ± 6.3 years, 70.5% males) with polysomnography-confirmed RBD who eventually phenoconverted to overt alpha-synucleinopathy (RBD due to synucleinopathy) were enrolled, and underwent baseline presynaptic dopaminergic imaging and clinical assessment, including motor, cognitive, olfaction, and constipation evaluation. For comparison, 232 RBD non-phenoconvertor patients (67.6 ± 7.1 years, 78.4% males) and 160 controls (68.2 ± 7.2 years, 53.1% males) were enrolled. Imaging and clinical features were analyzed by machine learning to determine predictors of phenoconversion. RESULTS: Machine learning analysis showed that clinical data alone poorly predicted phenoconversion. Presynaptic dopaminergic imaging significantly improved the prediction, especially in combination with clinical data, with 77% sensitivity and 85% specificity in differentiating RBD due to synucleinopathy from non phenoconverted RBD patients, and 85% sensitivity and 86% specificity in discriminating PD-converters from DLB-converters. Quantification of presynaptic dopaminergic imaging showed that an empirical z-score cutoff of -1.0 at the most affected hemisphere putamen characterized RBD due to synucleinopathy patients, while a cutoff of -1.0 at the most affected hemisphere putamen/caudate ratio characterized PD-converters. INTERPRETATION: Clinical data alone poorly predicted phenoconversion in RBD due to synucleinopathy patients. Conversely, presynaptic dopaminergic imaging allows a good prediction of forthcoming phenoconversion diagnosis. This finding may be used in designing future disease-modifying trials. ANN NEUROL 2024;95:1178-1192.
- MeSH
- demence s Lewyho tělísky * diagnostické zobrazování MeSH
- dopamin * metabolismus MeSH
- jednofotonová emisní výpočetní tomografie MeSH
- lidé středního věku MeSH
- lidé MeSH
- Parkinsonova nemoc * diagnostické zobrazování komplikace MeSH
- porucha chování v REM spánku * diagnostické zobrazování MeSH
- presynaptické terminály metabolismus MeSH
- senioři MeSH
- strojové učení * MeSH
- synukleinopatie * diagnostické zobrazování MeSH
- zobrazení dopaminergního systému MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
BACKGROUND: Only few data are available on treatment-associated behavior of distinct rare CNS embryonal tumor entities previously treated as "CNS-primitive neuroectodermal tumors" (CNS-PNET). Respective data on specific entities, including CNS neuroblastoma, FOXR2 activated (CNS NB-FOXR2), and embryonal tumors with multilayered rosettes (ETMR) are needed for development of differentiated treatment strategies. METHODS: Within this retrospective, international study, tumor samples of clinically well-annotated patients with the original diagnosis of CNS-PNET were analyzed using DNA methylation arrays (n = 307). Additional cases (n = 66) with DNA methylation pattern of CNS NB-FOXR2 were included irrespective of initial histological diagnosis. Pooled clinical data (n = 292) were descriptively analyzed. RESULTS: DNA methylation profiling of "CNS-PNET" classified 58 (19%) cases as ETMR, 57 (19%) as high-grade glioma (HGG), 36 (12%) as CNS NB-FOXR2, and 89(29%) cases were classified into 18 other entities. Sixty-seven (22%) cases did not show DNA methylation patterns similar to established CNS tumor reference classes. Best treatment results were achieved for CNS NB-FOXR2 patients (5-year PFS: 63% ± 7%, OS: 85% ± 5%, n = 63), with 35/42 progression-free survivors after upfront craniospinal irradiation (CSI) and chemotherapy. The worst outcome was seen for ETMR and HGG patients with 5-year PFS of 18% ± 6% and 22% ± 7%, and 5-year OS of 24% ± 6% and 25% ± 7%, respectively. CONCLUSION: The historically reported poor outcome of CNS-PNET patients becomes highly variable when tumors are molecularly classified based on DNA methylation profiling. Patients with CNS NB-FOXR2 responded well to current treatments and a standard-risk CSI-based regimen may be prospectively evaluated. The poor outcome of ETMR across applied treatment strategies substantiates the necessity for evaluation of novel treatments.
- MeSH
- forkhead transkripční faktory MeSH
- germinální a embryonální nádory * diagnóza genetika terapie MeSH
- lidé MeSH
- molekulární patologie MeSH
- nádory centrálního nervového systému * diagnóza genetika terapie MeSH
- nádory mozku * diagnóza genetika terapie MeSH
- primitivní neuroektodermové nádory * diagnóza genetika terapie MeSH
- retrospektivní studie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
- MeSH
- autofagie * fyziologie MeSH
- autofagozomy MeSH
- biologické markery MeSH
- biotest normy MeSH
- lidé MeSH
- lyzozomy MeSH
- proteiny spojené s autofagií metabolismus MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
- směrnice MeSH
