ArticlemedRxiv : the preprint server for health sciences2024
Genome-wide DNA methylation markers associated with metabolic liver cancer.
Article in medRxiv : the preprint server for health sciences, 2024. 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
- Updated by
Authors and funding
17 authors.
Funding
Abstract
Background and Aims: Metabolic liver disease is the fastest rising cause of hepatocellular carcinoma (HCC) worldwide, but the underlying molecular processes that drive HCC development in the setting of metabolic perturbations are unclear. We investigated the role of aberrant DNA methylation in metabolic HCC development in a multicenter international study. Methods: We used a case-control design, frequency-matched on age, sex, and study site. Genome-wide profiling of peripheral blood leukocyte DNA was performed using the 850k EPIC array. Cell type proportions were estimated from the methylation data. The study samples were split 80% and 20% for training and validation. Differential methylation analysis was performed with adjustment for cell type, and we generated area under the receiver-operating curves (ROC-AUC). Results: We enrolled 272 metabolic HCC patients and 316 control patients with metabolic liver disease from six sites. Fifty-five differentially methylated CpGs were identified; 33 hypermethylated and 22 hypomethylated in cases versus controls. The panel of 55 CpGs discriminated between cases and controls with AUC=0.79 (95%CI=0.71-0.87), sensitivity=0.77 (95%CI=0.66-0.89), and specificity=0.74 (95%CI=0.64-0.85). The 55-CpG classifier panel performed better than a base model that comprised age, sex, race, and diabetes mellitus (AUC=0.65, 95%CI=0.55-0.75, sensitivity=0.62 (95%CI=0.49-0.75) and specificity=0.64 (95%CI=0.52-0.75). A multifactorial model that combined the 55 CpGs with age, sex, race, and diabetes, yielded AUC=0.78 (95%CI=0.70-0.86), sensitivity=0.81 (95%CI=0.71-0.92), and specificity=0.67 (95%CI=0.55-0.78). Conclusions: A panel of 55 blood leukocyte DNA methylation markers differentiates patients with metabolic HCC from control patients with benign metabolic liver disease, with a slightly higher sensitivity when combined with demographic and clinical information.
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.