Synergistic Interaction Between PEAR1-FGB and the Dominant Role of ABCB1 in Thrombosis Risk: A SHAP and MDR-Based...

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.

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).

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.

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.

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.