ArticleFrontiers in immunology2022
Diagnostic model constructed by nine inflammation-related genes for diagnosing ischemic stroke and reflecting the condition of immune-related cells.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Systematic review and meta-analysis of stroke blood biomarker data highlights need for more translational research methods.Nature communications · 2026Pooled it
- Proteomic Mendelian randomization and machine learning reveal causal plasma biomarkers in cardiorenal comorbidity.Renal failure · 2026Article
- Elucidation of key lactylation- and palmitoylation-related genes and their related mechanisms in the development of neuropathic pain.Medicine · 2026Article
- Abundance of Inflammatory Response Genes Among Cardiovascular Disease and Ischemic Stroke Genes.International journal of molecular sciences · 2026Article
- Identification and validation of genes associated with mitochondria in cerebral infarction and benign prostatic hyperplasia.Frontiers in medicine · 2026Article
- Predicting cerebral infarction and transient ischemic attack in healthy individuals and those with dysmetabolism: a machine learning approach combined with routine blood tests.Scientific reports · 2025Article
- Combined Analysis of Human and Experimental Rat Samples Identified Biomarkers for Ischemic Stroke.Molecular neurobiology · 2025Article
- Machine learning analysis of gene expression profiles of pyroptosis-related differentially expressed genes in ischemic stroke revealed potential targets for drug repurposing.Scientific reports · 2025Article
- Differential effects of Mediterranean vs. Western diets on coronary atherosclerosis and peripheral artery transcriptomics.Frontiers in nutrition · 2025Article
- Potential diagnostic biomarkers for immunogenic cell death in elderly female patients with ischemic stroke: identification and analysis.Scientific reports · 2024Article
- Immune-Related MoleculesInternational journal of molecular sciences · 2024Article
- Assessing the impact of novel risk loci on Alzheimer's and Parkinson's diseases in a Chinese Han cohort.Frontiers in neurology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Ischemic cerebral infarction is the most common type of stroke with high rates of mortality, disability, and recurrence. However, the known diagnostic biomarkers and therapeutic targets for ischemic stroke (IS) are limited. In the current study, we aimed to identify novel inflammation-related biomarkers for IS using machine learning analysis and to explore their relationship with the levels of immune-related cells in whole blood samples. Methods: Gene expression profiles of healthy controls and patients with IS were download from the Gene Expression Omnibus. Analysis of differentially expressed genes (DEGs) was performed in healthy controls and patients with IS. Single-sample gene set enrichment analysis was performed to calculate inflammation scores, and weighted gene co-expression network analysis was used to analyze genes in significant modules associated with inflammation scores. Key DEGs in significant modules were then analyzed using LASSO regression analysis for constructing a diagnostic model. The effectiveness and specificity of the diagnostic model was verified in healthy controls and patients with IS and with cerebral hemorrhage (CH) using qRT-PCR. The relationship between diagnostic score and the levels of immune-related cells in whole blood were analyzed using Pearson correlations. Results: A total of 831 DEGs were identified. Both chronic and acute inflammation scores were higher in patients with IS, while 54 DEGs were also clustered in the gene modules associated with chronic and acute inflammation scores. Among them, a total of 9 genes were selected to construct a diagnostic model. Interestingly, RT-qPCR showed that the diagnostic model had better diagnostic value for IS but not for CH. The levels of lymphocytes were lower in blood of patients with IS, while the levels of monocytes and neutrophils were increased. The diagnostic score of the model was negatively associated with the levels of lymphocytes and positively associated with levels of monocytes and neutrophils. Conclusions: Taken together, the diagnostic model constructed using the inflammation-related genes
Indexed as
Identifiers
What OpenQuestion holds
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.