Muscarinic Receptors Expression in the Peripheral Blood Cells Differentiate Dementia with Lewy Bodies from Alzheimer’s Disease
Authors: Reale, Marcella | Carrarini, Claudia | Russo, Mirella | Dono, Fedele | Ferri, Laura | Di Pietro, Martina | Costantini, Erica | Porreca, Annamaria | Di Nicola, Marta | Onofrj, Marco | Bonanni, Laura
Article Type: Research Article
Abstract: Background: Central nervous system disruption of cholinergic (ACh) signaling, which plays a major role in cognitive processes, is well documented in dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD). The expression of muscarinic ACh receptors type 1 and 4 (CHRM1 and CHRM4) has been reported to be altered in the brain of DLB patients. Objective: We aim to assess the peripheral gene expression of CHRM1 and 4 in DLB as a possible marker as compared to AD and healthy control (HC) subjects. Methods: Peripheral blood mononuclear cells were collected from 21 DLB, 13 AD, and 8 HC matched subjects. …RT-PCR was performed to estimate gene expression of CHRM1 and CHRM4. Results: Peripheral CHRM1 expression was higher and CHRM4 was lower in DLB and AD compared to HC, whereas both CHRM1 and CHRM4 levels were higher in AD compared to DLB patients. Receiver operating characteristics curves, with logistic regression analysis, showed that combining peripheral CHRM1 and CHRM4 levels, DLB and AD subjects were classified with an accuracy of 76.0%. Conclusion: Alterations of peripheral CHRM1 and CHRM4 was found in both AD and DLB patients as compared to HC. CHRM1 and CHRM4 gene expression resulted to be lower in DLB patients compared to AD. In the future, peripheral CHRM expression could be studied as a possible marker of neurodegenerative conditions associated with cholinergic deficit and a possible marker of response to acetylcholinesterase inhibitors. Show more
Keywords: Alzheimer’s disease, cholinergic imbalance, dementia with Lewy bodies, muscarinic receptors, real time-polymerase chain reaction
DOI: 10.3233/JAD-215285
Citation: Journal of Alzheimer's Disease, vol. 85, no. 1, pp. 323-330, 2022
A Machine Learning-Based Holistic Approach to Predict the Clinical Course of Patients within the Alzheimer’s Disease Spectrum 1
Authors: Massetti, Noemi | Russo, Mirella | Franciotti, Raffaella | Nardini, Davide | Mandolini, Giorgio Maria | Granzotto, Alberto | Bomba, Manuela | Delli Pizzi, Stefano | Mosca, Alessandra | Scherer, Reinhold | Onofrj, Marco | Sensi, Stefano L.
Article Type: Research Article
Abstract: Background: Alzheimer’s disease (AD) is a neurodegenerative condition driven by multifactorial etiology. Mild cognitive impairment (MCI) is a transitional condition between healthy aging and dementia. No reliable biomarkers are available to predict the conversion from MCI to AD. Objective: To evaluate the use of machine learning (ML) on a wealth of data offered by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and Alzheimer’s Disease Metabolomics Consortium (ADMC) database in the prediction of the MCI to AD conversion. Methods: We implemented an ML-based Random Forest (RF) algorithm to predict conversion from MCI to AD. Data related to the study population (587 MCI …subjects) were analyzed by RF as separate or combined features and assessed for classification power. Four classes of variables were considered: neuropsychological test scores, AD-related cerebrospinal fluid (CSF) biomarkers, peripheral biomarkers, and structural magnetic resonance imaging (MRI) variables. Results: The ML-based algorithm exhibited 86% accuracy in predicting the AD conversion of MCI subjects. When assessing the features that helped the most, neuropsychological test scores, MRI data, and CSF biomarkers were the most relevant in the MCI to AD prediction. Peripheral parameters were effective when employed in association with neuropsychological test scores. Age and sex differences modulated the prediction accuracy. AD conversion was more effectively predicted in females and younger subjects. Conclusion: Our findings support the notion that AD-related neurodegenerative processes result from the concerted activity of multiple pathological mechanisms and factors that act inside and outside the brain and are dynamically affected by age and sex. Show more
Keywords: Alzheimer’s disease, conversion, dementia, machine learning, mild cognitive impairment, random forest
DOI: 10.3233/JAD-210573
Citation: Journal of Alzheimer's Disease, vol. 85, no. 4, pp. 1639-1655, 2022
A Young Man with Cognitive Impairment and a Heart Condition
Authors: Russo, Mirella | Santilli, Matteo | De Rosa, Matteo A. | Calisi, Dario | Dono, Fedele | Mattoli, Maria Vittoria | Bonanni, Laura | Onofrj, Marco | Sensi, Stefano L.
Article Type: Short Communication
Abstract: A 43-year-old came to our observation for progressive cognitive impairment, confirmed by the neuropsychological evaluation. A diagnosis of multidomain amnestic mild cognitive impairment, due to unknown reasons, was posited at the first assessment. The patient’s neurological exam was otherwise completely normal. The patient’s mother was clinically diagnosed with frontotemporal dementia in her forties. The patient underwent neuroimaging investigations and cerebrospinal fluid analysis. Our diagnostic work-up pointed toward a neurodegenerative etiology, but the presence of concurrent cardiomyopathy emerged in the meantime. Due to the patient’s family history, a thorough genetic screening was performed. The results revealed a unique genetic asset, with …heterozygotic variants of three amyloid-related genes (PSEN1 , APP , and MYBPC3 ). PSEN1 and MYBPC3 mutations showed distinct pathogenic features and accounted for the patient’s brain and cardiac amyloidosis, whereas the APP variant was of uncertain pathological implications. Show more
Keywords: cardiomyopathy, early onset dementia, mild cognitive impairment, neurodegeneration
DOI: 10.3233/JAD-220528
Citation: Journal of Alzheimer's Disease, vol. 89, no. 2, pp. 405-410, 2022
Plasma Neurofilament Light Chain Predicts Cognitive Progression in Prodromal and Clinical Dementia with Lewy Bodies
Authors: Pilotto, Andrea | Imarisio, Alberto | Carrarini, Claudia | Russo, Mirella | Masciocchi, Stefano | Gipponi, Stefano | Cottini, Elisabetta | Aarsland, Dag | Zetterberg, Henrik | Ashton, Nicholas J. | Hye, Abdul | Bonanni, Laura | Padovani, Alessandro
Article Type: Short Communication
Abstract: Plasma neurofilament light chain (NfL) is a marker of neuronal damage in different neurological disorders and might predict disease progression in dementia with Lewy bodies (DLB). The study enrolled 45 controls and 44 DLB patients (including 17 prodromal cases) who underwent an extensive assessment at baseline and at 2 years follow-up. At baseline, plasma NfL levels were higher in both probable DLB and prodromal cases compared to controls. Plasma NfL emerged as the best predictor of cognitive decline compared to age, sex, and baseline severity variables. The study supports the role of plasma NfL as a useful prognostic biomarker from …the early stages of DLB. Show more
Keywords: Biomarkers, cognitive progression, dementia with Lewy bodies, neurofilament light chain
DOI: 10.3233/JAD-210342
Citation: Journal of Alzheimer's Disease, vol. 82, no. 3, pp. 913-919, 2021
EEG Abnormalities During Delirium as a Prodromal Feature of Dementia with Lewy Bodies: A Case Report
Authors: Carrarini, Claudia | De Rosa, Matteo Alessandro | Calisi, Dario | Digiovanni, Anna | Salute, Pierpaolo | Dono, Fedele | Evangelista, Giacomo | Consoli, Stefano | Russo, Mirella | Ferri, Laura | D’Ardes, Damiano | Mattoli, Maria Vittoria | Cipollone, Francesco | Onofrj, Marco | Bonanni, Laura
Article Type: Research Article
Abstract: Background: A 79-year-old woman was admitted to the Neurology Clinic of the University of Chieti-Pescara for a syncope. At admission, the occurrence of an acute stroke was ruled out. Her cognitive status was unimpaired. After three days from the hospitalization, the patient experienced an episode of mixed delirium. Objective: The present case report shows a case of delirium-onset dementia with Lewy bodies (DLB) with a specific electroencephalographic (EEG) pattern from its prodromal stage. Methods: Delirium was assessed by 4AT test. During the hospitalization, the patient underwent a quantitative EEG (QEEG) with spectral analysis. At six months from the episode of …delirium, she was tested by neuropsychological evaluation, QEEG, and 18 F-fluorodeoxyglucose PET/CT to assess the onset of a possible cognitive decline. Results: At baseline, the QEEG exam showed a dominant frequency (DF) in the pre-alpha band (7.5 Hz) with a dominant frequency variability (DFV) of 2 Hz. This pattern is typical of DLB at early stage. After six months, she reported attention deficits in association with cognitive fluctuation and REM sleep behavior disorder. The neurological examination revealed signs of parkinsonism. Cognitive status resulted to be impaired (MoCA = 15/30). QEEG recording confirmed the presence of a DLB-typical pattern (DF = 7.5 Hz, DFV = 2.5 Hz). The 18 F-FDG-PET/CT showed a moderate bilateral posterior hypometabolism (occipital and temporal cortex), with relative sparing of the posterior cingulate cortex compared to cuneus/precuneus (Cingulate Island sign ), and mild bilateral hypometabolism in frontal regions (suggestive of a DLB diagnosis). Conclusion: EEGs may represent supportive and validated biomarkers for delirium-onset prodromal DLB. Show more
Keywords: Delirium, dementia with Lewy bodies, EEG, prodromal dementia
DOI: 10.3233/ADR-220017
Citation: Journal of Alzheimer's Disease Reports, vol. 6, no. 1, pp. 223-228, 2022
