ArticleJournal of blood medicine2026
Synergistic Interaction Between PEAR1-FGB and the Dominant Role of ABCB1 in Thrombosis Risk: A SHAP and MDR-Based Study in Vietnamese Pedigrees.
Article in Journal of blood medicine, 2026. 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
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: Thrombosis is a multifactorial disorder with a substantial genetic component, yet gene-gene interactions contributing to thrombotic risk remain insufficiently characterized in Southeast Asian populations. Identifying both individual genetic determinants and interaction effects may improve risk stratification, particularly in families with early-onset thrombotic disease. Objective: This study aimed to explore individual and interactive genetic contributions to thrombotic events in Vietnamese pedigrees with early-onset venous thromboembolism (VTE) using an integrated analytical framework combining Multifactor Dimensionality Reduction (MDR) and SHapley Additive exPlanations (SHAP). Methods: A pedigree-based study was conducted among 88 individuals from families with a history of early-onset VTE (<50 years), including 19 affected cases. Genetic variants were identified using next-generation sequencing. Random Forest modeling with SHAP was used to quantify global and local feature contributions, while MDR was applied to detect potential non-linear gene-gene interactions beyond single-locus effects. The Random Forest model was not explicitly adjusted for familial clustering or relatedness; results were therefore interpreted as exploratory. Results: SHAP analysis identified rs1045642 (ABCB1) as the strongest contributor to model-predicted baseline thrombotic risk. MDR analysis suggested that this background susceptibility may be further modified by a two-locus interaction between rs12041331 (PEAR1) and rs1800790 (FGB). Individuals classified within the high-risk MDR genotype combination showed increased odds of thrombosis (OR = 8.00, 95% CI: 1.67-74.96; p = 0.0028), compared with the corresponding single-locus model (OR = 3.73, 95% CI: 0.93-21.48; p = 0.0405). Confidence intervals were wide, reflecting limited precision. Conclusion: In this exploratory pedigree-based study, rs1045642 (ABCB1) was associated with baseline thrombotic susceptibility, while a potential interaction between PEAR1 and FGB may further modulate risk in specific genotype combinations. The integration of MDR and SHAP provides an interpretable framework for investigating complex genetic architectures. However, given the small sample size and limited number of events, these findings should be considered hypothesis-generating and require validation in larger independent cohorts.
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.