Development and validation of a genetic probability for venous thromboembolism
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background Factor V Leiden (FVL) and prothrombin gene mutations (PGMs), as well as recently developed polygenic scores (PGSs), have been consistently associated with venous thromboembolism (VTE) risk in European ancestry populations. Objectives This study aimed to develop an optimized risk-assessment tool combining mutations and PGS for diverse ancestry populations. Methods The association of VTE risk with FVL/PGM and PGS was tested using multivariable analyses in the UK Biobank. A genetic probability for VTE (GenProb-VTE) combining PGS and FVL/PGM was developed. Its discriminative and reclassification performances over FVL/PGM alone were assessed using observed VTE rate and the continuous net reclassification index, respectively. Results were validated in the Genomic Health Initiative of Endeavor Health, an ancestry-diverse health care system–based biobank. Results Among 432,831 participants in the UK Biobank, FVL, PGM, and PGS were significantly and independently associated with VTE risk ( P < .001). Compared with FVL/PGM alone, GenProb-VTE identified 1.5 times more high-risk subjects whose observed VTE rates exceeded those of FVL/PGM carriers. GenProb-VTE also significantly reclassified VTE risk from the model with FVL/PGM alone, with continuous net reclassification index of 0.10 ( P < .001). VTE risk was reclassified in FVL/PGM heterozygous carriers (51%) and homozygous/compound heterozygous carriers (46%) as well as noncarriers (14%). These results were validated among 16,341 participants in the Genomic Health Initiative, in participants of both European and non-European ancestry. Conclusion GenProb-VTE, an optimized tool combining PGS with FVL/PGM, significantly improves VTE risk assessment compared with FVL/PGM alone in diverse ancestry populations. It provides a novel tool for genetic risk assessment of VTE.
Authors: Zhuqing Shi, Ashley J. Mulford, Huy Tran, Michal Filipczak, Song Gao, Stevie Xie, Jason Lobel, Jun Wei, Andrew S. Rifkin, Annabelle Ashworth, Siqun Lilly Zheng, Clay Wiske, David Duggan, Brian T. Helfand, Arman Qamar, Alan R. Sanders, Alfonso J. Tafur, Jianfeng Xu
Language: English
Subfield: Hematology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,250
OpenAlex ID: W4409860182
