Special Issue "Early Recognition of Alzheimer´s Disease"

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurodegenerative Diseases".

Deadline for manuscript submissions: 10 December 2021.

Special Issue Editors

Prof. Dr. Lawrence J. Whalley
E-Mail Website
Guest Editor
Professor emeritus of mental health, Institute of Applied Health Sciences, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZH, Germany
Interests: brain aging; cohort studies; epidemiology; intelligence; childhood adversity
Prof. Dr. Johannes Schröder
E-Mail Website
Guest Editor
Section of Geriatric Psychiatry, University of Heidelberg, Voss Str. 4, 69115 Heidelberg, Germany
Interests: aging; mild cognitive impairment; cognitive reserve; linguistic changes; neurological soft signs

Special Issue Information

Dear Colleagues,

The discovery of a cholinergic deficit in Alzheimer's Disease has driven over 40 years of progress in understanding the neurobiology of clinical dementia syndromes. Landmark discoveries in neurogenetics, molecular neurobiology, and clinical neuropsychology have revealed new research questions. The early recognition of progress to dementia remains a critical limiting step in navigating ways towards new treatments, and the delay or even prevention of dementia onset. In this collection of invited papers, these questions and the implications of their possible answers are set out.

Pathways that lead to a better understanding of early Alzheimer’s Disease, that improve methods of early detection, clinical practice, and conduct of clinical trials will be considered in this Special Issue of Brain Sciences. We are looking forward to hearing from you soon.

Prof. Dr. Lawrence J. Whalley
Prof. Dr. Johannes Schröder
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Brain Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mild cognitive impairment
  • cognitive reserve
  • early recognition
  • risk factors
  • Alzheimer´s disease

Published Papers (3 papers)

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Research

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Article
fMRI Investigation of Semantic Lexical Processing in Healthy Control and Alzheimer’s Disease Subjects Using Naming Task: A Preliminary Study
Brain Sci. 2021, 11(6), 718; https://doi.org/10.3390/brainsci11060718 - 28 May 2021
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Abstract
For decades, scientists have been trying to solve the problem of dementia, with no cure currently available. Semantic–lexical impairment is well established as the early critical sign of dementia, although there are still gaps in knowledge that must be investigated. In this study, [...] Read more.
For decades, scientists have been trying to solve the problem of dementia, with no cure currently available. Semantic–lexical impairment is well established as the early critical sign of dementia, although there are still gaps in knowledge that must be investigated. In this study, we used fMRI to observe the neural activity of 31 subjects, including 16 HC (Healthy Control) and 15 AD (Alzheimer’s Disease), who participated in the naming task. The neuropsychology profile of HC (Healthy Control) and AD (Alzheimer’s Disease) are discussed in this study. The involvement of FG (Fusiform Gyrus) and IFG (Inferior Frontal Gyrus) shows dominant activation in both of the groups. We observed a decrease in neural activity in the AD group, resulting in semantic deficit problems in this preliminary study. Furthermore, ROI analysis was performed and revealed both hyperactivation and hypoactivation in the AD group. The compensatory mechanism demonstrated during the task, due to the effort required to identify an animal’s name, represents the character profile of AD. Full article
(This article belongs to the Special Issue Early Recognition of Alzheimer´s Disease)
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Article
Predicting Conversion from MCI to AD Combining Multi-Modality Data and Based on Molecular Subtype
Brain Sci. 2021, 11(6), 674; https://doi.org/10.3390/brainsci11060674 - 21 May 2021
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Abstract
Alzheimer’s disease (AD) is a neurodegenerative brain disease in the elderly. Identifying patients with mild cognitive impairment (MCI) who are more likely to progress to AD is a key step in AD prevention. Recent studies have shown that AD is a heterogeneous disease. [...] Read more.
Alzheimer’s disease (AD) is a neurodegenerative brain disease in the elderly. Identifying patients with mild cognitive impairment (MCI) who are more likely to progress to AD is a key step in AD prevention. Recent studies have shown that AD is a heterogeneous disease. In this study, we propose a subtyping-based prediction strategy to predict the conversion from MCI to AD in three years according to MCI patient subtypes. Structural magnetic resonance imaging (sMRI) data and multi-omics data, including genotype data and gene expression profiling derived from peripheral blood samples, from 125 MCI patients were used in the Alzheimer’s Disease Neuroimaging Initiative (ADNI)-1 dataset and from 98 MCI patients in the ADNI-GO/2 dataset. A variational Bayes approximation model based on the multiple kernel learning method was constructed to predict whether an MCI patient will progress to AD within three years. In internal fivefold cross-validation within ADNI-1, we achieved an overall AUC of 0.83 (79.20% accuracy, 81.25% sensitivity, 77.92% specificity) compared to the model without subtyping, which achieved an AUC of 0.78 (76.00% accuracy, 77.08% sensitivity, 75.32% specificity). In external validation using ADNI-1 as a training set and ADNI-GO/2 as an independent test set, we attained an AUC of 0.78 (74.49% accuracy, 74.19% sensitivity, 74.63% specificity). Identifying MCI patient subtypes with omics data would improve the accuracy of predicting the conversion from MCI to AD. In addition to evaluating statistics, obtaining the significant sMRI, single nucleotide polymorphism (SNP) and mRNA expression data from peripheral blood of MCI patients is noninvasive and cost-effective for predicting conversion from MCI to AD. Full article
(This article belongs to the Special Issue Early Recognition of Alzheimer´s Disease)
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Case Report
A Pathogenic Presenilin-1 Val96Phe Mutation from a Malaysian Family
Brain Sci. 2021, 11(10), 1328; https://doi.org/10.3390/brainsci11101328 - 08 Oct 2021
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Abstract
Presenilin-1 (PSEN1) is one of the causative genes for early onset Alzheimer’s disease (EOAD). Recently, emerging studies have reported several novel PSEN1 mutations among Asians. In this study, a PSEN1 Val96Phe mutation was discovered in two siblings from Malaysia with a [...] Read more.
Presenilin-1 (PSEN1) is one of the causative genes for early onset Alzheimer’s disease (EOAD). Recently, emerging studies have reported several novel PSEN1 mutations among Asians. In this study, a PSEN1 Val96Phe mutation was discovered in two siblings from Malaysia with a strong family history of disease. This is the second report of PSEN1 Val96Phe mutation among EOAD patients in Asia and in the world. Patients presented symptomatic changes in their behaviors and personality, such as apathy and withdrawal in their 40s. Previous cellular studies with COS1 cell lines revealed the mutation increased the amyloid-β42 (Aβ42) productions. In the present study, whole-exome sequencing was performed on the two siblings with EOAD, and they were analyzed against the virtual panel of 100 genes from various neurodegenerative diseases. In silico modeling was also performed on PSEN1 Val96Phe mutation. This mutation was located on the first transmembrane helix of PSEN1 protein, resulting significant intramolecular stresses in the helices. This helical domain would play a significant role in γ-secretase cleavage for the increased Aβ42 productions. Several other adjacent mutations were reported in this helical domain, including Ile83Thr or Val89Leu. Our study suggested that perturbations in TMI-HLI-TMII regions could also be associated with C-terminal fragment accumulation of APP and enhanced amyloid productions. Full article
(This article belongs to the Special Issue Early Recognition of Alzheimer´s Disease)
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