ArticleFrontiers in neurology
Identification of key genes and metabolites in acute ischemic stroke via integrated transcriptomic and metabolomic analysis.
Article in Frontiers in neurology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Acute ischaemic stroke (AIS) remains a leading cause of death and disability. This exploratory study integrated transcriptomic and metabolomic analyses to identify candidate hub genes and metabolites associated with AIS and to provide preliminary insights into its molecular mechanisms and potential therapeutic targets. Methods: Metabolomic sequencing data were analyzed using orthogonal partial least squares discriminant analysis (OPLS-DA), together with multivariate and univariate analyses, to identify differentially expressed metabolites (DEMs). Differential gene expression analysis was performed using the GSE16561 dataset, and key genes were screened through protein-protein interaction network analysis, machine learning, expression validation, and diagnostic evaluation. Co-enrichment analysis of key genes and DEMs was then conducted, followed by immune infiltration analysis, molecular network construction, drug prediction, and RT-qPCR validation. Results: A total of 103 and 51 DEMs were identified in the positive and negative ion modes, respectively, and were mainly enriched in steroid hormone biosynthesis. Five key genes-ITGAM, TLR4, MMP9, STAT3, and TLR2-were identified as significantly dysregulated in AIS and showed good diagnostic performance. RT-qPCR confirmed increased expression of TLR4, MMP9, and TLR2 in AIS, whereas ITGAM and STAT3 showed inverse trends. Joint enrichment analysis indicated that key genes and DEMs were mainly involved in 30 pathways, including the HIF-1 and FoxO signaling pathways. Immune infiltration analysis showed that ITGAM had the strongest negative correlation with memory B cells ( Conclusion: This exploratory study identified candidate hub genes and metabolites associated with AIS and highlighted their related pathways, immune features, molecular networks, and candidate drugs. These findings provide preliminary insights into the molecular basis and potential therapeutic targets of AIS.
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.