ArticleFrontiers in genetics2021
Discovery and Validation of Key Biomarkers Based on Immune Infiltrates in Alzheimer's Disease.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it, 68 citations in OpenAlex.
- Identification of 16 novel Alzheimer's disease loci using multi-ancestry meta-analyses.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Pooled it
- Predicting diagnostic gene biomarkers associated with immune infiltration in patients with diabetes.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas · 2026Article
- Identification and Verification of Immune Metabolism-Related Biomarkers and Immune Infiltration Landscape for Pediatric Opsoclonus Myoclonus Ataxia Syndrome in Neuroblastoma.CNS neuroscience & therapeutics · 2025Article
- Hypoxic Natural Killer Cells-Derived HIF-1α-Containing Exosomes Inhibit Cellular Senescence and Apoptosis in Neurocytes to Ameliorate Alzheimer's Disease by Eliminating Oxidative Damages.Molecular neurobiology · 2025Article
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- Integrated bulk and single cell sequencing with experimental validation identifies type 2 diabetes biomarkers.Scientific reports · 2025Article
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- Identification and Experimental Validation of Biomarkers Related to MiR-125a-5p in Chronic Obstructive Pulmonary Disease.International journal of chronic obstructive pulmonary disease · 2025Article
- Establishment and Validation of the Diagnostic Value of Oligodendrocyterelated Genes in Alzheimer's Disease.CNS & neurological disorders drug targets · 2025Article
- Identification and validation of pyroptosis-related genes in Alzheimer's disease based on multi-transcriptome and machine learning.Frontiers in aging neuroscience · 2025Article
- Development of a Novel Mitochondrial Dysfunction-Related Alzheimer's Disease Diagnostic Model Using Bioinformatics and Machine Learning.Current Alzheimer research · 2025Article
- The Use of Machine Learning in the Diagnosis of Kidney Allograft Rejection: Current Knowledge and Applications.Diagnostics (Basel, Switzerland) · 2024Review
- Review
- Identification of 16 novel Alzheimer's disease susceptibility loci using multi-ancestry meta-analyses of clinical Alzheimer's disease and AD-by-proxy cases from four whole genome sequencing datasets.medRxiv : the preprint server for health sciences · 2024Article
- Neuroinflammation in Alzheimer's disease: insights from peripheral immune cells.Immunity & ageing : I & A · 2024Review
- Integration of National Health Insurance claims data and animal models reveals fexofenadine as a promising repurposed drug for Parkinson's disease.Journal of neuroinflammation · 2024Article
- Decreased TLR7 expression was associated with airway eosinophilic inflammation and lung function in asthma: evidence from machine learning approaches and experimental validation.European journal of medical research · 2024Article
- Peripheral blood amyloid-β involved in the pathogenesis of Alzheimer's disease via impacting on peripheral innate immune cells.Journal of neuroinflammation · 2024Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAs the most common neurodegenerative disease, Alzheimer's disease (AD) leads to progressive loss of cognition and memory. Presently, the underlying pathogenic genes of AD patients remain elusive, and effective disease-modifying therapy is not available. This study explored novel biomarkers that can affect diagnosis and treatment in AD based on immune infiltration.
methodsThe gene expression profiles of 139 AD cases and 134 normal controls were obtained from the NCBI GEO public database. We applied the computational method CIBERSORT to bulk gene expression profiles of AD to quantify 22 subsets of immune cells. Besides, based on the use of the Least Absolute Shrinkage Selection Operator (LASSO), this study also applied SVM-RFE analysis to screen key genes. GO-based semantic similarity and logistic regression model analyses were applied to explore hub genes further.
resultsThere was a remarkable significance in the infiltration of immune cells between the subgroups. The proportions for monocytes, M0 macrophages, and dendritic cells in the AD group were significantly higher than those in the normal group, while the proportion of some cells was lower than that of the normal group, such as NK cell resting, T-cell CD4 naive, T-cell CD4 memory activation, and eosinophils. Additionally, seven genes (ABCA2, CREBRF, CD72, CETN2, KCNG1, NDUFA2, and RPL36AL) were identified as hub genes. Then we performed the analysis of immune factor correlation, gene set enrichment analysis (GSEA), and GO based on seven hub genes. The AUC of ROC prediction model in test and validation sets were 0.845 and 0.839, respectively. Eventually, the mRNA expression analysis of ABCA2, NDUFA2, CREBRF, and CD72 revealed significant differences among the seven hub genes and then was confirmed by RT-PCR.
conclusionA model based on immune cell infiltration might be used to forecast AD patients' diagnosis, and it provided a new perspective for AD treatment targets.
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