ArticleAging2020
A model integrating donor gene polymorphisms predicts fibrosis after liver transplantation.
Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- A Comprehensive Review of Liver Allograft Fibrosis and Steatosis: From Cause to Diagnosis.Transplantation direct · 2023Review
- Associations of minor histocompatibility antigens with outcomes following allogeneic hematopoietic cell transplantation.American journal of hematology · 2023Article
- A model integrated fibrinogen and D-dimer for prediction of hepatocellular carcinoma recurrence following liver transplantation: a multicentre study.American journal of translational research · 2022Article
- Single-Nucleotide Polymorphisms Within Non-HLA Regions Are Associated With Engraftment Effectiveness for Patients With Unrelated Cord Blood Transplantation.Frontiers in immunology · 2022Article
- Genetic polymorphisms of CaFrontiers in endocrinology · 2022Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Post-transplant liver fibrosis (PTLF) is a common and severe complication in liver recipients. In this study, we assessed the impact of donor liver genetics on the development of PTLF. A total of 232 patients undergoing liver transplantation were included. Twenty-two single nucleotide polymorphisms (SNPs) associated with liver fibrosis were analyzed. Univariate analysis revealed seven donor SNPs to be associated with PTLF. In a multivariate analysis, independent risk factors of PTLF were genetic variation of donor GRP78 rs430397 (OR = 8.99, p = 0.003), GSTP1 rs1695 (OR = 0.13, p = 0.021), miRNA-196a rs12304647 (OR = 16.01, p =0.001), and TNF-α rs1800630 (OR = 79.78, p = 0.001); blood tacrolimus levels at maintenance > 7 ng/ml (OR =7.48, p <0.001); and post-transplant diabetes mellitus (OR = 7.50, p = 0.001). A predictive model that included donor SNPs showed better prognostic ability for PTLF than a model with only clinical parameters (AUROC: 0.863 vs 0.707, P < 0.001). Given that donor gene SNPs are associated with an increased risk of PTLF, this model integrated with donor gene polymorphisms may help clinicians predict PTLF.
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