Unsuspected involvement of spinal cord in Alzheimer Disease

Lorenzi, Roberta Maria; Palesi, Fulvia; Castellazzi, Gloria; Vitali, Paolo; Anzalone, Nicoletta; Bernini, Sara; Sinforiani, Elena; Micieli, Giuseppe; Costa, Alfredo; D’Angelo, Egidio; Wheeler-Kingshott, C

doi:10.1101/673350

Cited by 6 publications

(6 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CG, FP and RL wrote the manuscript, with comments from all other authors. This manuscript has been released as a Pre-Print at BioRxiv (Lorenzi et al, 2019).…”

Section: Author Contributionsmentioning

confidence: 99%

Unsuspected Involvement of Spinal Cord in Alzheimer Disease

Lorenzi

Palesi

Castellazzi

et al. 2020

Front. Cell. Neurosci.

Self Cite

View full text Add to dashboard Cite

Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and vice-versa, it is indeed a very interesting question to assess whether it is affected by atrophy due to a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We, therefore, hypothesize that in Alzheimer's disease (AD), severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia. Methods: 3DT1 images of 31 AD and 35 healthy control (HC) subjects were processed to calculate volume of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord [per vertebra as well as the C2-C3 pair (CSA23 and CSV23)]. Correlated features (ρ > 0.7) were removed, and the best subset identified for patients' classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p ≤ 0.05). Linear regression was implemented to assess the explained variance of the Mini-Mental State Examination (MMSE) score as a dependent variable with the best features as predictors. Results: Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and gray matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance. Discussion: Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. The results show that CSA23, calculated from the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further

show abstract

“…CG, FP and RL wrote the manuscript, with comments from all other authors. This manuscript has been released as a Pre-Print at BioRxiv (Lorenzi et al, 2019).…”

Section: Author Contributionsmentioning

confidence: 99%

Unsuspected Involvement of Spinal Cord in Alzheimer Disease

Lorenzi

Palesi

Castellazzi

et al. 2020

Front. Cell. Neurosci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Sixty patients affected by neurodegenerative diseases were recruited at the IRCCS Mondino Foundation, as part of a study on cognitive impairment published in Palesi et al 24 , Castellazzi et al 28 , Lorenzi et al 29 , Pizzarotti et al 25 . The study was carried out in accordance with the Declaration of Helsinki with written informed consent from all subjects.…”

Section: Methodsmentioning

confidence: 99%

Subject-specific features of excitation/inhibition profiles in neurodegenerative diseases

Monteverdi¹,

Palesi

Costa

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Brain pathologies are based on microscopic changes in neurons and synapses that reverberate into large scale networks altering brain dynamics and functional states. An important yet unresolved issue concerns the impact of patients excitation/inhibition profiles on neurodegenerative diseases including Alzheimer's disease, Frontotemporal Dementia and Amyotrophic Lateral Sclerosis. In this work we used a simulation platform, The Virtual Brain, to simulate brain dynamics in healthy controls and in Alzheimer's disease, Frontotemporal Dementia and Amyotrophic Lateral Sclerosis patients. The brain connectome and functional connectivity were extracted from 3T-MRI scans and The Virtual Brain nodes were represented by a Wong-Wang neural mass model endowing an explicit representation of the excitatory/inhibitory balance. The integration of cerebro-cerebellar loops improved the correlation between experimental and simulated functional connectivity, and hence The Virtual Brain predictive power, in all pathological conditions. The Virtual Brain biophysical parameters differed between clinical phenotypes, predicting higher global coupling and inhibition in Alzheimer's disease and stronger NMDA (N-methyl-D-aspartate) receptor-dependent excitation in Amyotrophic Lateral Sclerosis. These physio-pathological parameters allowed an advanced analysis of patients' state. In backward regressions, The Virtual Brain parameters significantly contributed to explain the variation of neuropsychological scores and, in discriminant analysis, the combination of The Virtual Brain parameters and neuropsychological scores significantly improved discriminative power between clinical conditions. Eventually, cluster analysis provided a unique description of the excitatory/inhibitory balance in individual patients. In aggregate, The Virtual Brain simulations reveal differences in the excitatory/inhibitory balance of individual patients that, combined with cognitive assessment, can promote the personalized diagnosis and therapy of neurodegenerative diseases.

show abstract

“…Extraventricular CSF, including cisterna magna and cranial CSF SAS , expands at a different rate than ventricular CSF and is 21% larger in AD patients compared to CHE. No quantitative information were available on spinal CSF SAS expansion, it can, however, be deduced that it might increase in AD as a consequence of the decrease of spinal cord volume (66), and it was, therefore, assumed to increase at the same rate as cranial CSF SAS .…”

Section: Csf Volumementioning

confidence: 99%

Drug Distribution in Brain and Cerebrospinal Fluids in Relation to IC50 Values in Aging and Alzheimer’s Disease, Using the Physiologically Based LeiCNS-PK3.0 Model

et al. 2022

View full text Add to dashboard Cite

Background Very little knowledge exists on the impact of Alzheimer’s disease on the CNS target site pharmacokinetics (PK). Aim To predict the CNS PK of cognitively healthy young and elderly and of Alzheimer’s patients using the physiologically based LeiCNS-PK3.0 model. Methods LeiCNS-PK3.0 was used to predict the PK profiles in brain extracellular (brainECF) and intracellular (brainICF) fluids and cerebrospinal fluid of the subarachnoid space (CSFSAS) of donepezil, galantamine, memantine, rivastigmine, and semagacestat in young, elderly, and Alzheimer’s patients. The physiological parameters of LeiCNS-PK3.0 were adapted for aging and Alzheimer’s based on an extensive literature search. The CNS PK profiles at plateau for clinical dose regimens were related to in vitro IC50 values of acetylcholinesterase, butyrylcholinesterase, N-methyl-D-aspartate, or gamma-secretase. Results The PK profiles of all drugs differed between the CNS compartments regarding plateau levels and fluctuation. BrainECF, brainICF and CSFSAS PK profile relationships were different between the drugs. Aging and Alzheimer’s had little to no impact on CNS PK. Rivastigmine acetylcholinesterase IC50 values were not reached. Semagacestat brain PK plateau levels were below the IC50 of gamma-secretase for half of the interdose interval, unlike CSFSAS PK profiles that were consistently above IC50. Conclusion This study provides insights into the relations between CNS compartments PK profiles, including target sites. CSFSAS PK appears to be an unreliable predictor of brain PK. Also, despite extensive changes in blood-brain barrier and brain properties in Alzheimer’s, this study shows that the impact of aging and Alzheimer’s pathology on CNS distribution of the five drugs is insignificant.

show abstract

Unsuspected involvement of spinal cord in Alzheimer Disease

Cited by 6 publications

References 43 publications

Unsuspected Involvement of Spinal Cord in Alzheimer Disease

Unsuspected Involvement of Spinal Cord in Alzheimer Disease

Subject-specific features of excitation/inhibition profiles in neurodegenerative diseases

Drug Distribution in Brain and Cerebrospinal Fluids in Relation to IC50 Values in Aging and Alzheimer’s Disease, Using the Physiologically Based LeiCNS-PK3.0 Model

Contact Info

Product

Resources

About