Estimating heritability of survival traits using censored multiple variance component model

TL;DR

This paper introduces a scalable, robust statistical model for estimating the heritability of survival traits with right-censoring in large biobank data, overcoming limitations of previous methods.

Contribution

The authors develop a censored multiple variance component model that accurately estimates heritability of survival traits in large-scale datasets with high censoring rates.

Findings

Accurately estimates heritability at up to 80% censoring.

Computationally efficient for large datasets with a million subjects.

Provides a robust framework applicable to biobank-scale genetic studies.

Abstract

Characterizing the genetic basis of survival traits, such as age at disease onset, is critical for risk stratification, early intervention, and elucidating biological mechanisms that can inform therapeutic development. However, time-to-event outcomes in human cohorts are frequently right-censored, complicating both the estimation and partitioning of total heritability. Modern biobanks linked to electronic health records offer the unprecedented power to dissect the genetic basis of age-at-diagnosis traits at large scale. Yet, few methods exist for estimating and partitioning the total heritability of censored survival traits. Existing methods impose restrictive distributional assumptions on genetic and environmental effects and are not scalable to large biobanks with a million subjects. We introduce a censored multiple variance component model to robustly estimate the total heritability of survival traits under right-censoring. We demonstrate through extensive simulations that the method provides accurate total heritability estimates of right-censored traits at censoring rates up to 80% given sufficient sample size. The method is computationally efficient in estimating one hundred genetic variance components of a survival trait using large-scale biobank genotype data consisting of a million subjects and a million SNPs in under nine hours, including uncertainty quantification. We apply our method to estimate the total heritability of four age-at-diagnosis traits from the UK Biobank study. Our results establish a scalable and robust framework for heritability analysis of right-censored survival traits in large-scale genetic studies.