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Boosting power for time-to-event GWAS analysis affected by case ascertainment

We propose a computationally efficient genome-wide association study (GWAS) method, WtCoxG, for time-to-event (TTE) traits in the presence of case ascertainment— a form of oversampling bias. WtCoxG addresses case ascertainment bias by applying a weighted Cox proportional hazard model, and outperforms existing approaches when incorporating information on external allele frequencies.

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Fig. 1: Pipeline of WtCoxG method.

References

  1. Bi, W., Fritsche, L. G., Mukherjee, B., Kim, S. & Lee, S. A fast and accurate method for genome-wide time-to-event data analysis and its application to UK Biobank. Am. J. Hum. Genet. 107, 222–233 (2020). This paper presents SPACox, a scalable and accurate framework for survival analysis GWAS methods in biobank-scale studies.

    Article  Google Scholar 

  2. Dey, R. et al. Efficient and accurate frailty model approach for genome-wide survival association analysis in large-scale biobanks. Nat. Commun. 13, 5437 (2022). This paper developed a frailty model approach that enhances statistical power in survival GWASs.

    Article  Google Scholar 

  3. Pedersen, E. M., et al. ADuLT: An efficient and robust time-to-event GWAS. Nat. Commun. 14, 5553 (2023). This paper proposed ADuLT, a GWAS method correcting for case ascertainment based on a liability threshold model.

    Article  Google Scholar 

  4. Ma, Y., Zhao, Y., Zhang, J.-F. & Bi, W. Efficient and accurate framework for genome-wide gene-environment interaction analysis in large-scale biobanks. Nat. Commun. 16, 3064 (2025). This paper presents SPAGxE, a method for gene–environment interactions under a retrospective framework.

    Article  Google Scholar 

  5. Xu, H. et al. SPAGRM: effectively controlling for sample relatedness in large-scale genome-wide association studies of longitudinal traits. Nat. Commun. 16, 1413 (2025). This paper presents SPAGRM, a method that effectively accounts for sample relatedness under a retrospective framework.

    Article  Google Scholar 

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This is a summary of: Li, Y. et al. Applying weighted Cox regression to genome-wide association studies of time-to-event phenotypes. Nat. Comput. Sci. https://doi.org/10.1038/s43588-025-00864-z (2025).

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Boosting power for time-to-event GWAS analysis affected by case ascertainment. Nat Comput Sci (2025). https://doi.org/10.1038/s43588-025-00892-9

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