Mixture cure model with an application to interval mapping of quantitative trait loci

Area of Science:

• Genetics
• Biostatistics
• Quantitative Trait Loci (QTL) Analysis

Background:

• Mapping quantitative trait loci (QTL) with censored time-to-event data is complicated by nonsusceptible subjects.
• Ignoring heterogeneous susceptibility can lead to missed genetic discoveries or false positives.

Purpose of the Study:

• To propose an interval mapping method using parametric mixture cure models to address challenges posed by nonsusceptible subjects in QTL analysis.
• To detect QTL influencing differential susceptibility and/or time-to-event trait distribution.

Main Methods:

• Development of an interval mapping method based on parametric mixture cure models.
• Implementation of a likelihood-based testing procedure.
• Calculation of genome-wide significance levels using a resampling method.

Main Results:

• The proposed method effectively accounts for nonsusceptible subjects in QTL mapping.
• Simulation studies and a real-data application demonstrate the method's performance.
• The importance of considering heterogeneous susceptibility is highlighted.

Conclusions:

• The proposed parametric mixture cure model approach provides a robust framework for QTL mapping with censored time-to-event data in the presence of nonsusceptible individuals.
• Accurate identification of genetic factors influencing susceptibility and survival is enhanced by accounting for non-susceptibility.