ReviewJournal of clinical and translational hepatology2022
Recent Progress and Future Direction for the Application of Multiomics Data in Clinical Liver Transplantation.
Review in Journal of clinical and translational hepatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Complex impacts of gallstone disease on metabolic syndrome and nonalcoholic fatty liver disease.Frontiers in endocrinology · 2022Pooled it
- Surveillance and prevention of infection in clinical xenotransplantation.Clinical microbiology reviews · 2025Review
- Molecular Mechanisms of Ischemia/Reperfusion Injury and Graft Dysfunction in Liver Transplantation: Insights from Multi-Omics Studies in Rodent Animal Models.International journal of biological sciences · 2025Review
- Advanced omics approaches in liver transplant settings: current applications and future prospectives.Frontiers in immunology · 2025Review
- Integrated multi-omic analysis identifies fatty acid binding protein 4 as a biomarker and therapeutic target of ischemia-reperfusion injury in steatotic liver transplantation.Cellular and molecular life sciences : CMLS · 2024Article
- A Comprehensive Review of Liver Allograft Fibrosis and Steatosis: From Cause to Diagnosis.Transplantation direct · 2023Review
- Editorial: Systems biology approach for the mechanisms underlying chronic liver disease.Frontiers in medicine · 2022Article
- Graft-to-recipient weight ratio exerts nonlinear effects on prognosis by interacting with donor liver macrosteatosis.Frontiers in surgery · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Omics data address key issues in liver transplantation (LT) as the most effective therapeutic means for end-stage liver disease. The purpose of this study was to review the current application and future direction for omics in LT. We reviewed the use of multiomics to elucidate the pathogenesis leading to LT and prognostication. Future directions with respect to the use of omics in LT are also described based on perspectives of surgeons with experience in omics. Significant molecules were identified and summarized based on omics, with a focus on post-transplant liver fibrosis, early allograft dysfunction, tumor recurrence, and graft failure. We emphasized the importance omics for clinicians who perform LTs and prioritized the directions that should be established. We also outlined the ideal workflow for omics in LT. In step with advances in technology, the quality of omics data can be guaranteed using an improved algorithm at a lower price. Concerns should be addressed on the translational value of omics for better therapeutic effects in patients undergoing LT.
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.