Dataset Information

Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.

ABSTRACT: Utilizing the publicly available neuroimaging database enabled by Alzheimer's disease Neuroimaging Initiative (ADNI; http://adni.loni.usc.edu/ ), we have compared the performance of automated classification algorithms that differentiate AD vs. normal subjects using Positron Emission Tomography (PET) with fluorodeoxyglucose (FDG). General linear model, scaled subprofile modeling and support vector machines were examined. Among the tested classification methods, support vector machine with Iterative Single Data Algorithm produced the best performance, i.e., sensitivity (0.84)?×?specificity (0.95), by 10-fold cross-validation. We have applied the same classification algorithm to four different datasets from ADNI, Health Science Centre (Winnipeg, Canada), Dong-A University Hospital (Busan, S. Korea) and Asan Medical Centre (Seoul, S. Korea). Our data analyses confirmed that the support vector machine with Iterative Single Data Algorithm showed the best performance in prediction of future development of AD from the prodromal stage (mild cognitive impairment), and that it was also sensitive to other types of dementia such as Parkinson's Disease Dementia and Dementia with Lewy Bodies, and that perfusion imaging using single photon emission computed tomography may achieve a similar accuracy to that of FDG-PET.

SUBMITTER: Katako A

PROVIDER: S-EPMC6125295 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.

Katako Audrey A Shelton Paul P Goertzen Andrew L AL Levin Daniel D Bybel Bohdan B Aljuaid Maram M Yoon Hyun Jin HJ Kang Do Young DY Kim Seok Min SM Lee Chong Sik CS Ko Ji Hyun JH

Scientific reports 20180905 1

Utilizing the publicly available neuroimaging database enabled by Alzheimer's disease Neuroimaging Initiative (ADNI; http://adni.loni.usc.edu/ ), we have compared the performance of automated classification algorithms that differentiate AD vs. normal subjects using Positron Emission Tomography (PET) with fluorodeoxyglucose (FDG). General linear model, scaled subprofile modeling and support vector machines were examined. Among the tested classification methods, support vector machine with Iterati ...[more]

PMID: 30185806

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Project description:BackgroundParkinson's disease (PD) is a condition that affects movement and is usually seen in those over the age of 50. It is caused by the death of dopaminergic neurons, particularly in the substantia nigra. PD has shifted from being perceived as an uncommon condition to a significant neurological illness, mostly due to the increasing number of elderly individuals and the impact of environmental factors. Parkinson's plus syndromes, such as progressive supranuclear palsy (PSP), multiple system atrophy (MSA), corticobasal degeneration (CBD), and vascular Parkinsonism (VaP), provide difficulties in distinguishing them clinically from PD since they have similar characteristics.MethodologyA thorough examination was performed utilizing the PubMed, Medline, Scopus, and Web of Science databases. The search utilized specific keywords like "Parkinson's disease," "Parkinson's plus syndrome," "Lewy body dementia," "Alzheimer's dementia," "progressive supranuclear palsy," and "multiple system atrophy." The selection criteria were aimed at English-language literature, with a particular focus on examining the connection between PD and associated disorders or dementias.Results and discussionParkinson's plus syndromes, such as PSP, MSA, CBD, and VaP, exhibit unique clinical characteristics, imaging results, and diverse reactions to levodopa. This makes it difficult to distinguish them from PD. LBD is characterized by Lewy bodies containing α-synuclein, which leads to both motor and cognitive deficits. PD and Alzheimer's disease (AD) exhibit a complex interaction, including common pathogenic processes, genetic predispositions, and clinical characteristics of dementia.ConclusionThe interrelatedness of PD, Parkinson's plus syndromes, LBD, and AD highlights the significance of comprehending shared disease-causing processes. Aberrant protein clumping, impaired functioning of mitochondria, increased oxidative stress, and inflammation in the brain are common factors which can be addressed for specific treatments. More research is essential for understanding complicated connections and developing effective therapies for these sophisticated neurological illnesses.

Project description:As the differential diagnosis of dementias based on established clinical criteria is often difficult, biomarkers for applicable diagnostic testing are currently under intensive investigation. Amyloid plaques deposited in the brain of patients suffering from Alzheimer's disease, dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) mainly consist of carboxy-terminally elongated forms of amyloid-beta (Abeta) peptides, such as Abeta1-42. Absolute Abeta1-42 levels in CSF have shown diagnostic value for the diagnosis of Alzheimer's disease, but the discrimination among Alzheimer's disease, DLB and PDD was poor. A recently established quantitative urea-based Abeta-sodium-dodecylsulphate-polyacrylamide-gel-electrophoresis with Western immunoblot (Abeta-SDS-PAGE/immunoblot) revealed a highly conserved Abeta peptide pattern of the carboxy-terminally truncated Abeta peptides 1-37, 1-38, 1-39 in addition to 1-40 and 1-42 in human CSF. We used the Abeta-SDS-PAGE/immunoblot to investigate the CSF of 23 patients with Alzheimer's disease, 21 with DLB, 21 with PDD and 23 non-demented disease controls (NDC) for disease-specific alterations of the Abeta peptide patterns in its absolute and relative quantities. The diagnostic groups were matched for age and severity of dementia. The present study is the first attempt to evaluate the meaning of Abeta peptide patterns in CSF for differential diagnosis of the three neurodegenerative diseases--Alzheimer's disease, DLB and PDD. The Abeta peptide patterns displayed disease-specific variations and the ratio of the differentially altered Abeta1-42 to the Abeta1-37 levels subsequently discriminated all diagnostic groups from each other at a highly significant level, except DLB from PDD. Additionally, a novel peptide with Abeta-like immunoreactivity was observed constantly in the CSF of all 88 investigated patients. The pronounced percentage increase of this peptide in DLB allowed a highly significant discrimination from PDD. Using a cut-off point of 0.954%, this marker yielded a diagnostic sensitivity and specificity of 81 and 71%, respectively. From several lines of indication, we consider this peptide to represent an oxidized alpha-helical form of Abeta1-40 (Abeta1-40*). The increased abundance of Abeta1-40* probably reflects a disease-specific alteration of the Abeta1-40 metabolism in DLB. We conclude that Abeta peptide patterns reflect disease-specific pathophysiological pathways of different dementia syndromes as distinct neurochemical phenotypes. Although Abeta peptide patterns failed to fulfil the requirements for a sole biomarker, their combined evaluation with other biomarkers is promising in neurochemical dementia diagnosis. It is noteworthy that DLB and PDD exhibit distinct clinical temporal courses, despite their similar neuropathological appearance. Their distinct molecular phenotypes support the view of different pathophysiological pathways for each of these neurodegenerative diseases.

Project description:Swallowing dysfunction is an increasingly recognized problem in patients with dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD), which can result in aspiration pneumonia and death. Few studies have examined potential ways of improving swallowing function in this fragile patient group. The aim of this study was to evaluate swallowing dysfunction and carbonated liquid using videofluoroscopy in DLB and PDD patients.A total of 48 patients with DLB and PDD were referred for a clinical examination with videofluoroscopy. Descriptive overall assessments were provided at the time of the examination regarding swallowing function and the effects of different modifications, including carbonated thin liquid (CTL). Additionally, a repeated measures quantitative retrospective analysis has been performed comparing 1) thin liquids; 2) thickened liquids and 3) CTLs, with regard to the quantitative variables 1) pharyngeal transit time (PTT); 2) pharyngeal retention and 3) tracheal penetration.In all, 40/48 (83%) of the patients had a swallowing dysfunction, which was confirmed on videofluoroscopy, with 34/40 (85%) patients having a pharyngeal-type dysfunction. A total of 14/40 (35%) patients with an objective swallowing impairment did not have any subjective swallowing symptoms. Out of the patients with swallowing dysfunction, 87% had an overall improved swallowing function with carbonated liquid. PTT for carbonated liquid (median 633 ms, interquartile range [IQR] 516-786 ms) was quicker than for thin liquid (760 ms, IQR 613-940 ms, P=0.014) and thickened liquid (880.0 ms, IQR 600-1,500 ms, P<0.001). No significant effect was seen in residue or penetration.The majority of patients with DLB or PDD had a swallowing dysfunction, sometimes without subjective swallowing symptoms, which improved with carbonated liquid. This highlights the importance of investigating patients with videofluoroscopy and to carry out a prospective interventional study to further evaluate carbonated liquid, also addressing the effects on quality of life, aspiration and mortality.

Dataset Information

Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.

Publications

Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.

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