ArticleFrontiers in endocrinology2025
TRAF3IP2 as a novel inflammatory biomarker for coronary artery disease: development and validation of a multimodal prediction model.
Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Coronary artery disease (CAD) is currently among the leading cardiovascular diseases with considerable morbidity/mortality worldwide. While inflammation drives atherosclerosis, clinically actionable biomarkers remain elusive. The role of TRAF3IP2, a proinflammatory adaptor molecule, in the pathogenesis and prediction of coronary artery disease warrants systematic investigation. The purpose of this study was to explore the role of TRAF3IP2 in coronary artery disease and to develop and validate a nomogram for predicting the risk of coronary artery disease. Methods: GSE12288 gene expression profiles were downloaded from the Gene Expression Omnibus database, and key genes and pathways involved in CAD (n=222) were identified. LASSO and multivariate logistic regression analyses were applied to investigate the risk factors for severe coronary artery stenosis in a clinical cohort (n=280). A nomogram model was developed to predict CAD, and the clinical utility of the nomogram model was evaluated using calibration curves and decision curve analysis (DCA). Results: Multiple bioinformatics tools revealed that TRAF3IP2 expression was higher in patients with CAD than in controls. Moreover, TRAF3IP2 is involved in the cellular response to inflammation, which is a basic process of atherosclerosis. Clinical data from a total of 280 patients were retrospectively reviewed for our study. Sex (OR 0.446 [0.230-0.863], p=0.017), diabetes history (OR 2.099 [1.131-3.896], p=0.019), phosphoremia (OR 0.252 [0.065-0.972], p=0.045) and TRAF3IP2 (OR 1.040 [1.004-1.076], p=0.027) were independent risk factors for atherosclerosis. The nomogram was composed of these factors, and the calibration curves and DCA curve showed that the model has great potential for clinical utility. Conclusions: In summary, this study demonstrated that TRAF3IP2 could be a potential biomarker for CAD. A nomogram composed of sex, diabetes history, phosphoremia, and TRAF3IP2 expression may predict the risk of CAD.
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.