ArticleScientific reports2018
Systematic Analysis and Biomarker Study for Alzheimer's Disease.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled it.
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Who cites it
43 citing papers in PubMed, 2 syntheses or guidelines pooled it, 84 citations in OpenAlex.
- Meta-Analysis of Transcriptomic Studies of Blood and Six Brain Regions Identifies a Consensus of 15 Cross-Tissue Mechanisms in Alzheimer's Disease and Suggests an Origin of Cross-Study Heterogeneity.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2025Pooled it
- Meta-Analysis of Gene Expression Changes in the Blood of Patients with Mild Cognitive Impairment and Alzheimer's Disease Dementia.International journal of molecular sciences · 2019Pooled it
- Artificial Intelligence for Alzheimer's Disease Diagnosis: From Traditional Machine Learning to Large Language Models.Biosensors · 2026Review
- LASSO-HHO two-stage hybrid gene selection framework for accurate Alzheimer's disease diagnosis.Scientific reports · 2026Article
- Cell-type-aware transcriptome-wide association studies identify 91 independent risk genes for Alzheimer's disease dementia.Communications biology · 2026Article
- TYK2 mediates neuroinflammation in Alzheimer's disease brains with TDP-43 pathology.Nature communications · 2026Article
- Diagnosis of Alzheimer's disease with high accuracy via Petri net modeling of signaling pathways.Scientific reports · 2026Article
- Homocysteine interferes with Ndufa1 leading to mitochondrial dysfunction through repression of the NADCell death & disease · 2025Article
- Tensor decomposition of multi-dimensional splicing events across multiple tissues to identify splicing-mediated risk genes associated with complex traits.PLoS computational biology · 2025Article
- Transcriptomic predictors of rapid progression from mild cognitive impairment to Alzheimer's disease.Alzheimer's research & therapy · 2025Article
- Blood-derived APLP1Science advances · 2025Article
- Infections withFrontiers in aging neuroscience · 2025Review
- Bioinformatics and experimental validation identify biomarkers for diagnosing Alzheimer's disease.Frontiers in aging neuroscience · 2025Article
- Deep learning-based Alzheimer's disease detection using magnetic resonance imaging and gene expression data.PloS one · 2025Article
- TYK2 as a novel therapeutic target in Alzheimer's Disease with TDP-43 inclusions.bioRxiv : the preprint server for biology · 2024Article
- Transcriptional risk scores in Alzheimer's disease: From pathology to cognition.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Identification of Blood Biomarkers Related to Energy Metabolism and Construction of Diagnostic Prediction Model Based on Three Independent Alzheimer's Disease Cohorts.Journal of Alzheimer's disease : JAD · 2024Article
- Deep Learning-Based Prediction of Alzheimer's Disease Using Microarray Gene Expression Data.Biomedicines · 2023Article
- Music compensates for altered gene expression in age-related cognitive disorders.Scientific reports · 2023Article
- A New Approach for Multimodal Usage of Gene Expression and Its Image Representation for the Detection of Alzheimer's Disease.Biomolecules · 2023Article
Corrections and comments
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Authors and funding
11 authors at 5 institutions in 2 countries.
Funding
Abstract
Revealing the relationship between dysfunctional genes in blood and brain tissues from patients with Alzheimer's Disease (AD) will help us to understand the pathology of this disease. In this study, we conducted the first such large systematic analysis to identify differentially expressed genes (DEGs) in blood samples from 245 AD cases, 143 mild cognitive impairment (MCI) cases, and 182 healthy control subjects, and then compare these with DEGs in brain samples. We evaluated our findings using two independent AD blood datasets and performed a gene-based genome-wide association study to identify potential novel risk genes. We identified 789 and 998 DEGs common to both blood and brain of AD and MCI subjects respectively, over 77% of which had the same regulation directions across tissues and disease status, including the known ABCA7, and the novel TYK2 and TCIRG1. A machine learning classification model containing NDUFA1, MRPL51, and RPL36AL, implicating mitochondrial and ribosomal function, was discovered which discriminated between AD patients and controls with 85.9% of area under the curve and 78.1% accuracy (sensitivity = 77.6%, specificity = 78.9%). Moreover, our findings strongly suggest that mitochondrial dysfunction, NF-κB signalling and iNOS signalling are important dysregulated pathways in AD pathogenesis.
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Registered trials
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 OpenQuestion graph.