ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2024
Using blood transcriptome analysis for Alzheimer's disease diagnosis and patient stratification.
Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 20 citations in OpenAlex.
- Multi-ancestry transcriptome-wide association study reveals shared and population-specific genetic effects in Alzheimer disease.American journal of human genetics · 2026Article
- Integrative bioinformatics and machine learning reveal an association of LTF and MMP8 with systemic inflammation and lung injury.Respiratory research · 2026Article
- Ethnic-specific effects of the LILRB2-LILRB5 locus and newly identified risk loci for Alzheimer's disease in the East Asian population.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Blood gene expression network expression strongly relates to brain amyloid burden.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Multi-ancestry Transcriptome-Wide Association Study Reveals Shared and Population-Specific Genetic Effects in Alzheimer's Disease.bioRxiv : the preprint server for biology · 2025Article
- Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions.Acta pharmaceutica Sinica. B · 2025Review
- Alzheimer's Disease: Treatment Challenges for the Future.Journal of neurochemistry · 2025Review
- Modernizing diagnosis of Alzheimer's disease: A review of global trends and Asia-specific perspectives.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Precision Neuro-Oncology in Glioblastoma: AI-Guided CRISPR Editing and Real-Time Multi-Omics for Genomic Brain Surgery.International journal of molecular sciences · 2025Review
- Cell type heterogeneity in gene co-expression networks: implications for toxicological research.Briefings in bioinformatics · 2025Review
- Identification of therapeutic targets for Alzheimer's Disease Treatment using bioinformatics and machine learning.Scientific reports · 2025Article
- Genome-wide transcriptome analysis of Aβ deposition on PET in a Korean cohort.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Using blood transcriptome analysis for Alzheimer's disease diagnosis and patient stratification.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
Corrections and comments
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Authors and funding
18 authors at 3 institutions in 6 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionBlood protein biomarkers demonstrate potential for Alzheimer's disease (AD) diagnosis. Limited studies examine the molecular changes in AD blood cells.
methodsBulk RNA-sequencing of blood cells was performed on AD patients of Chinese descent (n = 214 and 26 in the discovery and validation cohorts, respectively) with normal controls (n = 208 and 38 in the discovery and validation cohorts, respectively). Weighted gene co-expression network analysis (WGCNA) and deconvolution analysis identified AD-associated gene modules and blood cell types. Regression and unsupervised clustering analysis identified AD-associated genes, gene modules, cell types, and established AD classification models.
resultsWGCNA on differentially expressed genes revealed 15 gene modules, with 6 accurately classifying AD (areas under the receiver operating characteristics curve [auROCs] > 0.90). These modules stratified AD patients into subgroups with distinct disease states. Cell-type deconvolution analysis identified specific blood cell types potentially associated with AD pathogenesis. DISCUSSION: This study highlights the potential of blood transcriptome for AD diagnosis, patient stratification, and mechanistic studies. HIGHLIGHTS: We comprehensively analyze the blood transcriptomes of a well-characterized Alzheimer's disease cohort to identify genes, gene modules, pathways, and specific blood cells associated with the disease. Blood transcriptome analysis accurately classifies and stratifies patients with Alzheimer's disease, with some gene modules achieving classification accuracy comparable to that of the plasma ATN biomarkers. Immune-associated pathways and immune cells, such as neutrophils, have potential roles in the pathogenesis and progression of Alzheimer's disease.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.