ArticleCNS neuroscience & therapeutics2023
Integrated transcriptomics reveals the brain and blood biomarkers in Alzheimer's disease.
Article in CNS neuroscience & therapeutics, 2023. 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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13 citing papers in PubMed, 24 citations in OpenAlex.
- Evaluating Chronic Sex-Specific Changes in Glutamatergic Signaling Markers Following Traumatic Brain Injury.International journal of molecular sciences · 2026Article
- Impact of Klotho genotype on lactylation in Alzheimer's disease and mechanistic insights.Immunity & ageing : I & A · 2026Article
- Conserved Blood Transcriptome Patterns Highlight microRNA and Hub Gene Drivers of Neurodegeneration.Genes · 2025Article
- Integrated transcriptomics of multiple sclerosis peripheral blood mononuclear cells explored potential biomarkers for the disease.Biochemistry and biophysics reports · 2025Article
- Integrative single-cell RNA sequencing and mendelian randomization analysis reveal the potential role of synaptic vesicle cycling-related genes in Alzheimer's disease.The journal of prevention of Alzheimer's disease · 2025Article
- Identification of UBE2N as a biomarker of Alzheimer's disease by combining WGCNA with machine learning algorithms.Scientific reports · 2025Article
- Integrated Transcriptome Analysis Reveals Novel Molecular Signatures for Schizophrenia Characterization.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Molecular pathogenesis of Alzheimer's disease onset in a mouse model: effects of cannabidiol treatment.Frontiers in neuroscience · 2025Article
- Identification of Autophagy-Related Candidate Genes in the Early Diagnosis of Alzheimer's Disease and Exploration of Potential Molecular Mechanisms.Molecular neurobiology · 2024Article
- SCG5 and MITF may be novel markers of copper metabolism immunorelevance in Alzheimer's disease.Scientific reports · 2024Article
- Integration of single-cell sequencing with machine learning and Mendelian randomization analysis identifies the NAP1L1 gene as a predictive biomarker for Alzheimer's disease.Frontiers in aging neuroscience · 2024Article
- Advances in Blood Biomarkers for Alzheimer's Disease: Ultra-Sensitive Detection Technologies and Impact on Clinical Diagnosis.Degenerative neurological and neuromuscular disease · 2024Review
- Integrated transcriptomics reveals the brain and blood biomarkers in Alzheimer's disease.CNS neuroscience & therapeutics · 2023Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe systematic molecular associations between the peripheral blood cells and brain in Alzheimer's disease (AD) remains unclear, which hinders our understanding of AD pathological mechanisms and the exploration of new diagnostic biomarkers.
methodsHere, we performed an integrated analysis of the brain and peripheral blood cells transcriptomics to establish peripheral biomarkers of AD. By employing multiple statistical analyses plus machine learning, we identified and validated multiple regulated central and peripheral network in patients with AD.
resultsBy bioinformatics analysis, a total of 243 genes were differentially expressed in the central and peripheral systems, mainly enriched in three modules: immune response, glucose metabolism and lysosome. In addition, lysosome related gene ATP6V1E1 and immune response related genes (IL2RG, OSM, EVI2B TNFRSF1A, CXCR4, STAT5A) were significantly correlated with Aβ or Tau pathology. Finally, receiver operating characteristic (ROC) analysis revealed that ATP6V1E1 showed high-diagnostic potential for AD.
conclusionTaken together, our data identified the main pathological pathways in AD progression, particularly the systemic dysregulation of the immune response, and provided peripheral biomarkers for AD diagnosis.
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