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Molecular Biomarkers in Alzheimer’s Disease
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Molecular Biomarkers in Alzheimer’s Disease

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Genetic Diagnosis".

Deadline for manuscript submissions: closed (25 July 2023) | Viewed by 9181

Special Issue Editor

Prof. Dr. Yongzhao Shao

E-Mail Website
Guest Editor
Department of Population Health, New York University, New York, NY 10003, USA
Interests: biostatistics; precision medicine; cancer epidemiology; clinical trials; environmental epidemiology; Alzheimer's disease; multi-center studies; gene-environment interaction; survival analysis

Special Issue Information

Dear Colleagues,

Alzheimer’s disease (AD) is a leading cause of death without effective treatments available. The vast majority of AD cases are late onset, where pathological changes begin many years before the presentation of clinical symptoms. Both predicting those at risk of AD and the segmentation of patients for clinical trials remain important challenges. The difficulties are partially due to the polygenic nature of AD, the complex gene–environment and gene–lifestyle factor interactions, as well as AD’s clinical heterogeneity. Additionally, as a common late-life disorder, AD often overlaps with age-associated neuropathologies, vascular disorders, and cognitive impairments. Biomarker studies are essential for the identification of a robust strategy for developing effective prevention, accurate diagnosis, and novel treatments for mild cognitive impairment (MCI), Alzheimer's disease, and Alzheimer's-disease-related dementias (ADRDs). The suitable topics for this Special Issue include but are not limited to:

  1. Genetic, transcriptomic, and epigenetic variants, eQTL, QTL, pathways, or gene networks associated with the risk or rate of progression of ADRD.
  2. Genomic, proteomic or multi-omic analysis of blood-based, CSF-based, or vascular biomarkers of neuroinflammation, neurodegeneration and risk of MCI or ADRD.
  3. Gene–environment and gene–lifestyle factor interactions and the prevention of neurodegeneration, MCI, or ADRD.
  4. Biomarkers of chronic mental-health disorders or sleep disorders for the risk of MCI or ADRD.
  5. Biomarkers or polygenic models for the prevention and treatment of MCI or ADRD.
  6. Biomarkers of longevity, normal aging, and age at onset of MCI or ADRD.

Prof. Dr. Yongzhao Shao
Guest Editor

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 submissions that pass pre-check are 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. Genes 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 2600 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

  • Alzheimer’s disease and related dementias
  • mild cognitive impairment
  • amyloid plaques
  • neurofibrillary tangles
  • abnormal phosphorylated tau
  • biomarkers of neurodegeneration
  • genetic susceptibility to AD
  • abnormal cognitive decline
  • ATN classification scheme in AD
  • gene-environment interaction in late-onset Alzheimer’s disease

Published Papers (4 papers)

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Research

20 pages, 7151 KiB  
Article
Metabolic Pathway Pairwise-Based Signature as a Potential Non-Invasive Diagnostic Marker in Alzheimer’s Disease Patients
by Yunwen Feng, Xingyu Chen, Xiaohua Douglas Zhang and Chen Huang
Genes 2023, 14(6), 1285; https://doi.org/10.3390/genes14061285 - 17 Jun 2023
Cited by 2 | Viewed by 1729
Abstract
Alzheimer’s disease (AD) is an incurable neurodegenerative disorder. Early screening, particularly in blood plasma, has been demonstrated as a promising approach to the diagnosis and prevention of AD. In addition, metabolic dysfunction has been demonstrated to be closely related to AD, which might [...] Read more.
Alzheimer’s disease (AD) is an incurable neurodegenerative disorder. Early screening, particularly in blood plasma, has been demonstrated as a promising approach to the diagnosis and prevention of AD. In addition, metabolic dysfunction has been demonstrated to be closely related to AD, which might be reflected in the whole blood transcriptome. Hence, we hypothesized that the establishment of a diagnostic model based on the metabolic signatures of blood is a workable strategy. To that end, we initially constructed metabolic pathway pairwise (MPP) signatures to characterize the interplay among metabolic pathways. Then, a series of bioinformatic methodologies, e.g., differential expression analysis, functional enrichment analysis, network analysis, etc., were used to investigate the molecular mechanism behind AD. Moreover, an unsupervised clustering analysis based on the MPP signature profile via the Non-Negative Matrix Factorization (NMF) algorithm was utilized to stratify AD patients. Finally, aimed at distinguishing AD patients from non-AD groups, a metabolic pathway-pairwise scoring system (MPPSS) was established using multi-machine learning methods. As a result, many metabolic pathways correlated to AD were disclosed, including oxidative phosphorylation, fatty acid biosynthesis, etc. NMF clustering analysis divided AD patients into two subgroups (S1 and S2), which exhibit distinct activities of metabolism and immunity. Typically, oxidative phosphorylation in S2 exhibits a lower activity than that in S1 and non-AD group, suggesting the patients in S2 might possess a more compromised brain metabolism. Additionally, immune infiltration analysis showed that the patients in S2 might have phenomena of immune suppression compared with S1 and the non-AD group. These findings indicated that S2 probably has a more severe progression of AD. Finally, MPPSS could achieve an AUC of 0.73 (95%CI: 0.70, 0.77) in the training dataset, 0.71 (95%CI: 0.65, 0.77) in the testing dataset, and an AUC of 0.99 (95%CI: 0.96, 1.00) in one external validation dataset. Overall, our study successfully established a novel metabolism-based scoring system for AD diagnosis using the blood transcriptome and provided new insight into the molecular mechanism of metabolic dysfunction implicated in AD. Full article
(This article belongs to the Special Issue Molecular Biomarkers in Alzheimer’s Disease)
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17 pages, 1243 KiB  
Article
Interaction between KLOTHO-VS Heterozygosity and APOE ε4 Allele Predicts Rate of Cognitive Decline in Late-Onset Alzheimer’s Disease
by Xi Richard Chen, Yongzhao Shao, Martin J. Sadowski and on behalf of the Alzheimer’s Disease Neuroimaging Initiative
Genes 2023, 14(4), 917; https://doi.org/10.3390/genes14040917 - 15 Apr 2023
Cited by 1 | Viewed by 1689
Abstract
KLOTHO-VS heterozygosity (KL-VShet+) promotes longevity and protects against cognitive decline in aging. To determine whether KL-VShet+ mitigates Alzheimer’s disease (AD) progression, we used longitudinal linear-mixed models to compare the rate of change in multiple cognitive measures [...] Read more.
KLOTHO-VS heterozygosity (KL-VShet+) promotes longevity and protects against cognitive decline in aging. To determine whether KL-VShet+ mitigates Alzheimer’s disease (AD) progression, we used longitudinal linear-mixed models to compare the rate of change in multiple cognitive measures in AD patients stratified by APOE ε4 carrier status. We aggregated data on 665 participants (208 KL-VShet−/ε4−, 307 KL-VShet−/ε4+, 66 KL-VShet+/ε4−, and 84 KL-VShet+/ε4+) from two prospective cohorts, the National Alzheimer’s Coordinating Center and the Alzheimer’s Disease Neuroimaging Initiative. All participants were initially diagnosed with mild cognitive impairment, later developed AD dementia during the study, and had at least three subsequent visits. KL-VShet+ conferred slower cognitive decline in ε4 non-carriers (+0.287 MMSE points/year, p = 0.001; −0.104 CDR-SB points/year, p = 0.026; −0.042 ADCOMS points/year, p < 0.001) but not in ε4 carriers who generally had faster rates of decline than non-carriers. Stratified analyses showed that the protective effect of KL-VShet+ was particularly prominent in male participants, those who were older than the median baseline age of 76 years, or those who had an education level of at least 16 years. For the first time, our study provides evidence that KL-VShet+ status has a protective effect on AD progression and interacts with the ε4 allele. Full article
(This article belongs to the Special Issue Molecular Biomarkers in Alzheimer’s Disease)
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15 pages, 2643 KiB  
Article
Deep Learning-Based Feature Extraction with MRI Data in Neuroimaging Genetics for Alzheimer’s Disease
by Dipnil Chakraborty, Zhong Zhuang, Haoran Xue, Mark B. Fiecas, Xiatong Shen and Wei Pan
Genes 2023, 14(3), 626; https://doi.org/10.3390/genes14030626 - 01 Mar 2023
Cited by 2 | Viewed by 2961
Abstract
The prognosis and treatment of patients suffering from Alzheimer’s disease (AD) have been among the most important and challenging problems over the last few decades. To better understand the mechanism of AD, it is of great interest to identify genetic variants associated with [...] Read more.
The prognosis and treatment of patients suffering from Alzheimer’s disease (AD) have been among the most important and challenging problems over the last few decades. To better understand the mechanism of AD, it is of great interest to identify genetic variants associated with brain atrophy. Commonly, in these analyses, neuroimaging features are extracted based on one of many possible brain atlases with FreeSurf and other popular software; this, however, may cause the loss of important information due to our incomplete knowledge about brain function embedded in these suboptimal atlases. To address the issue, we propose convolutional neural network (CNN) models applied to three-dimensional MRI data for the whole brain or multiple, divided brain regions to perform completely data-driven and automatic feature extraction. These image-derived features are then used as endophenotypes in genome-wide association studies (GWASs) to identify associated genetic variants. When we applied this method to ADNI data, we identified several associated SNPs that have been previously shown to be related to several neurodegenerative/mental disorders, such as AD, depression, and schizophrenia. Full article
(This article belongs to the Special Issue Molecular Biomarkers in Alzheimer’s Disease)
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12 pages, 1023 KiB  
Article
SORL1 Polymorphisms in Mexican Patients with Alzheimer’s Disease
by Danira Toral-Rios, Elizabeth Ruiz-Sánchez, Nancy Lucero Martínez Rodríguez, Marlene Maury-Rosillo, Óscar Rosas-Carrasco, Fernando Becerril-Pérez, Francisco Mena-Barranco, Rosa Carvajal-García, Daniela Silva-Adaya, Yair Delgado-Namorado, Gerardo Ramos-Palacios, Carmen Sánchez-Torres and Victoria Campos-Peña
Genes 2022, 13(4), 587; https://doi.org/10.3390/genes13040587 - 25 Mar 2022
Cited by 3 | Viewed by 2204
Abstract
The present study evaluated the risk effect of 12 Single Nucleotide Polymorphisms in the SORL1 gene in the Mexican population using Late-Onset Alzheimer’s Disease (LOAD) and control subjects. Considering APOE as the strongest genetic risk factor for LOAD, we conducted interaction analyses between [...] Read more.
The present study evaluated the risk effect of 12 Single Nucleotide Polymorphisms in the SORL1 gene in the Mexican population using Late-Onset Alzheimer’s Disease (LOAD) and control subjects. Considering APOE as the strongest genetic risk factor for LOAD, we conducted interaction analyses between single nucleotide polymorphisms (SNPs) and the APOE genotype. Methods: Patients were interviewed during their scheduled visits at neurologic and geriatric clinics from different institutions. The LOAD diagnosis included neurological, geriatric, and psychiatric examinations, as well as the medical history and neuroimaging. Polymorphisms in SORL1 were genotyped by real-time PCR in 156 subjects with LOAD and 221 controls. APOE genotype was determined in each study subject. Allelic, genotypic, and haplotypic frequencies were analyzed; an ancestry analysis was also performed. Results: The A/A genotype in rs1784933 might be associated with an increased LOAD risk. Two blocks with high degree linkage disequilibrium (LD) were identified. The first block composed by the genetic variants rs668387, rs689021 and rs641120 showed a positive interaction (mainly the rs689021) with rs1784933 polymorphism. Moreover, we found a significant association between the APOE ε4 allele carriers and the variant rs2070045 located in the second LD block. Conclusion: The rs1784933 polymorphism is associated with LOAD in Mexican patients. In addition, the presence of APOE ε4 allele and SORL1 variants could represent a genetic interaction effect that favors LOAD risk in the Mexican population. SNPs have been proposed as genetic markers associated with the development of LOAD that can support the clinical diagnosis. Future molecular studies could help understand sporadic Alzheimer’s Disease (AD) among the Mexican population, where currently there is a sub-estimate number in terms of disease frequency and incidence. Full article
(This article belongs to the Special Issue Molecular Biomarkers in Alzheimer’s Disease)
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