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Cited by 103Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsNeuroinflammation and Neurodegeneration Mechanisms

Identification of potential blood biomarkers for early diagnosis of Alzheimer’s disease through RNA sequencing analysis

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Shigemizu, Daichi, Mori, Taiki, Akiyama, Shintaro, Higaki, Sayuri, Watanabe, Hiroshi, Sakurai, Takashi, Niida, Shumpei, Ozaki, Kouichi·2020·Alzheimer's Research & Therapy
DOI 10.1186/s13195-020-00654-xPMC PMC7367375
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Abstract

Background: With demographic shifts toward older populations, the number of people with dementia is steadily increasing. Alzheimer’s disease (AD) is the most common cause of dementia, and no curative treatment is available. The current best strategy is to delay disease progression and to practice early intervention to reduce the number of patients that ultimately develop AD. Therefore, promising novel biomarkers for early diagnosis are urgently required. Methods: To identify blood-based biomarkers for early diagnosis of AD, we performed RNA sequencing (RNA-seq) analysis of 610 blood samples, representing 271 patients with AD, 91 cognitively normal (CN) adults, and 248 subjects with mild cognitive impairment (MCI). We first estimated cell-type proportions among AD, MCI, and CN samples from the bulk RNA-seq data using CIBERSORT and then examined the differentially expressed genes (DEGs) between AD and CN samples. To gain further insight into the biological functions of the DEGs, we performed gene set enrichment analysis (GSEA) and network-based meta-analysis. Results: In the cell-type distribution analysis, we found a significant association between the proportion of neutrophils and AD prognosis at a false discovery rate (FDR) < 0.05. Furthermore, a similar trend emerged in the results of routine blood tests from a large number of samples (n = 3,099: AD, 1,605; MCI, 994; CN, 500). In addition, GSEA and network-based meta-analysis based on DEGs between AD and CN samples revealed functional modules and important hub genes associated with the pathogenesis of AD. The risk prediction model constructed by using the proportion of neutrophils and the most important hub genes (EEF2 and RPL7) achieved a high AUC of 0.878 in a validation cohort; when further applied to a prospective cohort, the model achieved a high accuracy of 0.727. Conclusions: Our model was demonstrated to be effective in prospective AD risk prediction. These findings indicate the discovery of potential biomarkers for early diagnosis of AD, and their further improvement may lead to future practical clinical use.

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  • The second most significant CpG is located on the RPS8 gene, which encodes a ribosomal protein and was recently found to be significantly down-regulated in blood samples of AD patients.

    “The second most significant CpG is located on the RPS8 gene, which encodes a ribosomal protein and was recently found to be significantly down-regulated in blood samples of AD patients [77].”

    From Distinct sex-specific DNA methylation differences in Alzheimer’s disease (2022) · cites this paper as [77]

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Authors
Shigemizu, D., Mori, T., Akiyama, S., Higaki, S., Watanabe, H., Sakurai, T., Niida, S., & Ozaki, K.
Affiliations
  • Tokyo Medical and Dental University (JP)
  • Medical Genome Center, National Center for Geriatrics and Gerontology (JP)
  • Center for Comprehensive Care and Research on Memory Disorders, National Center for Geriatrics and Gerontology (JP)
  • RIKEN Center for Integrative Medical Sciences (JP)
Corresponding author
Shigemizu, Daichi
ORCID
Venue
Alzheimer's Research & Therapy
Publisher
Springer Science and Business Media LLC
Published
2020-07-16
Volume
12
Issue
1
Pages
87-87
ISSN
1758-9193 (ISSN-L)
DOI
10.1186/s13195-020-00654-x
PMC
PMC7367375
OpenAlex
W3043340891
Cited by
103
References
3
Citations by year
2026: 9 · 2025: 19 · 2024: 22 · 2023: 17 · 2022: 22 · 2021: 10 · 2020: 4
FWCI
2.23
Type
journal article
Language
en
Open access
Licence
Locations
  • Alzheimer s Research & Therapy (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Takeda Science Foundation
  • Ministry of Health, Labour and Welfare
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
Keywords
Alzheimer's disease, early diagnosis, blood biomarkers, neutrophil percentage, mild cognitive impairment, cell type deconvolution, differentially expressed genes, elongation factor 2, risk prediction model, hub genes, dementia
MeSH terms
Adult, Alzheimer Disease, Humans, Prospective Studies, Biomarkers, Sequence Analysis, RNA, Early Diagnosis, Cognitive Dysfunction

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