ArticleAmerican journal of human genetics2020
A Fast and Accurate Method for Genome-Wide Time-to-Event Data Analysis and Its Application to UK Biobank.
Article in American journal of human genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.
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Who cites it
57 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Limited overlap between genetic effects on disease susceptibility and disease survival.Nature genetics · 2025Article
- LDAK-KVIK performs fast and powerful mixed-model association analysis of quantitative and binary phenotypes.Nature genetics · 2025Article
- Gene-Diet Interaction Analysis in UK Biobank Identified Genetic Loci That Modify the Association Between Fish Oil Supplementation and the Incidence of Dementia.Current developments in nutrition · 2025Article
- Myeloid cell genome-wide screen identifies variants associated with Mycobacterium tuberculosis-induced cytokine transcriptional responses.The Journal of clinical investigation · 2025Article
- BAYESIAN VARIABLE SELECTION IN A COX PROPORTIONAL HAZARDS MODEL WITH THE "SUM OF SINGLE EFFECTS" PRIOR.ArXiv · 2025Article
- Combining genetic proxies of drug targets and time-to-event analyses from longitudinal observational data to identify target patient populations.BMC cardiovascular disorders · 2025 · on this mapObservational
- Polygenic risk scores for eGFR are associated with age at kidney failure.Journal of nephrology · 2025Article
- Efficient and accurate framework for genome-wide gene-environment interaction analysis in large-scale biobanks.Nature communications · 2025Article
- Genetic association studies using disease liabilities from deep neural networks.American journal of human genetics · 2025Article
- Exploring the protective role of maternal lung cancer history on allergic rhinitis.Journal of clinical biochemistry and nutrition · 2025Article
- Population-specific genetic-risk scores enable improved prediction of mortality within 28 days of sepsis onset: a retrospective Taiwanese cohort study.Journal of intensive care · 2025Article
- SPANature communications · 2025Article
- Donor and Recipient Polygenic Risk Scores Influence Kidney Transplant Function.Transplant international : official journal of the European Society for Organ Transplantation · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
With increasing biobanking efforts connecting electronic health records and national registries to germline genetics, the time-to-event data analysis has attracted increasing attention in the genetics studies of human diseases. In time-to-event data analysis, the Cox proportional hazards (PH) regression model is one of the most used approaches. However, existing methods and tools are not scalable when analyzing a large biobank with hundreds of thousands of samples and endpoints, and they are not accurate when testing low-frequency and rare variants. Here, we propose a scalable and accurate method, SPACox (a saddlepoint approximation implementation based on the Cox PH regression model), that is applicable for genome-wide scale time-to-event data analysis. SPACox requires fitting a Cox PH regression model only once across the genome-wide analysis and then uses a saddlepoint approximation (SPA) to calibrate the test statistics. Simulation studies show that SPACox is 76-252 times faster than other existing alternatives, such as gwasurvivr, 185-511 times faster than the standard Wald test, and more than 6,000 times faster than the Firth correction and can control type I error rates at the genome-wide significance level regardless of minor allele frequencies. Through the analysis of UK Biobank inpatient data of 282,871 white British European ancestry samples, we show that SPACox can efficiently analyze large sample sizes and accurately control type I error rates. We identified 611 loci associated with time-to-event phenotypes of 12 common diseases, of which 38 loci would be missed within a logistic regression framework with a binary phenotype defined as event occurrence status during the follow-up period.
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