ArticleFrontiers in immunology2026
Uncovering the pivotal role of MYO6 in myocardial infarction: a multimodally validated diagnostic biomarker and immunotherapeutic target.
Article in Frontiers in immunology, 2026. 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Myocardial infarction (MI) remains a leading cause of cardiovascular mortality worldwide, underscoring the need for improved diagnostic and therapeutic strategies. Despite recent in clinical management, delayed diagnosis and complications such as adverse myocardial remodeling continue to compromise long-term outcomes. Identifying specific biomarkers and actionable therapeutic targets is therefore crucial for precision medicine in MI. Methods: We integrated MI-related datasets from the Gene Expression Omnibus (GEO) database and performed differential expression analysis alongside weighted gene co-expression network analysis (WGCNA) to identify key differentially expressed genes (DEGs). Machine learning algorithms were applied to screen diagnostic hub genes and evaluate their diagnostic performance. Two-sample Mendelian randomization (MR) analysis, primarily utilizing the random-effects inverse-variance weighting assessed causal relationships between candidate genes and MI risk. Immune profiling was conducted via immune cell infiltration deconvolution and scRNA-seq analysis. Finally, wet-lab validation was performed using quantitative real-time PCR (RT-qPCR), Western blot, and immunohistochemistry in an Results: Our analysis initially identified 15 key diagnostic genes. Through two-sample MR analysis, MYO6 exhibited a significant causal relationship with a reduced risk of MI. Immune infiltration analysis revealed significant enrichment of pro-inflammatory cells (neutrophils and monocytes) and a concomitant depletion of protective immune cells (resting natural killer cells and activated CD4 memory T cells) in MI patients. MYO6 expression correlated positively with protective immune cells and negatively with pro-inflammatory cells. Furthermore, scRNA-seq analysis showed that MYO6 was predominantly enriched in T cells and natural killer cells, potentially regulating their subset differentiation, inhibiting excessive intercellular communication, and promoting collagen-mediated tissue repair, thereby alleviating MI injury and enhancing plaque stability. Conclusion: Through multidimensional analysis of clinical transcriptomic data and experimental validation in animal models, we have identified MYO6 as a potential novel diagnostic biomarker for MI, while highlighting the role of immune homeostasis in disease progression and MYO6 regulation. These findings provide crucial insights for the molecular diagnosis and targeted therapy of MI.
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.