ReviewActa neurochirurgica2021
"Omics" in traumatic brain injury: novel approaches to a complex disease.
Review in Acta neurochirurgica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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
10 citing papers in PubMed, 16 citations in OpenAlex.
- Updating Traumatic Brain Injury Classification for Surgeons: Integrating the CBI-M Framework Into Trauma and Acute Care Practice.World journal of surgery · 2026Review
- Hippocampal Bioenergetics and Metabolic Profiling Identifies Fatty Acid Oxidation as a Potential Therapeutic Target in Traumatic Brain Injury.Molecular neurobiology · 2026Article
- Personalized treatment approaches in neurocritical care.Acute and critical care · 2026Article
- Review
- Traumatic Brain Injury: Novel Experimental Approaches and Treatment Possibilities.Life (Basel, Switzerland) · 2025Review
- Neuroinflammation and acquired traumatic CNS injury: a mini review.Frontiers in neurology · 2024Review
- Polypathologies and Animal Models of Traumatic Brain Injury.Brain sciences · 2023Review
- Tandem Mass Tag-based proteomics analysis reveals the vital role of inflammation in traumatic brain injury in a mouse model.Neural regeneration research · 2023Article
- Review
- Progress Toward a Multiomic Understanding of Traumatic Brain Injury: A Review.Biomarker insights · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo date, there is neither any pharmacological treatment with efficacy in traumatic brain injury (TBI) nor any method to halt the disease progress. This is due to an incomplete understanding of the vast complexity of the biological cascades and failure to appreciate the diversity of secondary injury mechanisms in TBI. In recent years, techniques for high-throughput characterization and quantification of biological molecules that include genomics, proteomics, and metabolomics have evolved and referred to as omics.
methodsIn this narrative review, we highlight how omics technology can be applied to potentiate diagnostics and prognostication as well as to advance our understanding of injury mechanisms in TBI.
resultsThe omics platforms provide possibilities to study function, dynamics, and alterations of molecular pathways of normal and TBI disease states. Through advanced bioinformatics, large datasets of molecular information from small biological samples can be analyzed in detail and provide valuable knowledge of pathophysiological mechanisms, to include in prognostic modeling when connected to clinically relevant data. In such a complex disease as TBI, omics enables broad categories of studies from gene compositions associated with susceptibility to secondary injury or poor outcome, to potential alterations in metabolites following TBI.
conclusionThe field of omics in TBI research is rapidly evolving. The recent data and novel methods reviewed herein may form the basis for improved precision medicine approaches, development of pharmacological approaches, and individualization of therapeutic efforts by implementing mathematical "big data" predictive modeling in the near future.
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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.