Estimating the Heritability of Longitudinal Rate-of-Change: Genetic Insights into PSA Velocity in Prostate Cancer-Free Individuals

TL;DR

This study estimates the heritability of PSA velocity in prostate cancer-free men, revealing significant genetic influence and introducing efficient methods for large-scale genetic heritability analysis.

Contribution

It develops and applies two computational approaches to estimate heritability of PSA velocity from large longitudinal datasets, a novel contribution in this context.

Findings

Heritability of PSA velocity estimated at 0.45 (s.e. = 0.18).

Heritability of baseline PSA estimated at 0.32 (s.e. = 0.07).

Methods are unbiased and efficient for large datasets.

Abstract

Serum prostate-specific antigen (PSA) is widely used for prostate cancer screening. While the genetics of PSA levels has been studied to enhance screening accuracy, the genetic basis of PSA velocity, the rate of PSA change over time, remains unclear. The Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, a large, randomized study with longitudinal PSA data (15,260 cancer-free males, averaging 5.34 samples per subject) and genome-wide genotype data, provides a unique opportunity to estimate PSA velocity heritability. We developed a mixed model to jointly estimate heritability of PSA levels at age 54 and PSA velocity. To accommodate the large dataset, we implemented two efficient computational approaches: a partitioning and meta-analysis strategy using average information restricted maximum likelihood (AI-REML), and a fast restricted Haseman-Elston (REHE) regression method. Simulations showed that both methods yield unbiased estimates of both heritability metrics, with AI-REML providing smaller variability in the estimation of velocity heritability than REHE. Applying AI-REML to PLCO data, we estimated heritability at 0.32 (s.e. = 0.07) for baseline PSA and 0.45 (s.e. = 0.18) for PSA velocity. These findings reveal a substantial genetic contribution to PSA velocity, supporting future genome-wide studies to identify variants affecting PSA dynamics and improve PSA-based screening.