Characterization of genomic imprinting effects and patterns with parametric accelerated failure time model

Area of Science:

• Genetics
• Statistical Genetics
• Bioinformatics

Background:

• Genomic imprinting, where gene expression depends on parental origin, influences various biological traits.
• Understanding imprinted quantitative trait loci (iQTLs) is crucial for dissecting complex genetic architectures.
• Existing methods may not fully capture imprinting effects in survival traits.

Purpose of the Study:

• To develop a general parametric model for mapping imprinted quantitative trait loci (iQTLs) using survival analysis.
• To identify iQTLs associated with survival traits, specifically hyperoxic acute lung injury (HALI).
• To determine the optimal baseline hazard function for iQTL mapping in survival data.

Main Methods:

• Construction of a general parametric model based on the accelerated failure time model.
• Application of interval mapping and maximum likelihood estimation via the EM algorithm.
• Utilizing the Bayesian Information Criterion (BIC) for optimal baseline hazard function selection.

Main Results:

• The log-logistic distribution was identified as the optimal baseline hazard function for HALI survival data.
• Four quantitative trait loci (QTLs) influencing HALI survival were detected.
• Of the four identified QTLs, three exhibited imprinting, with distinct imprinting patterns, while one followed Mendelian inheritance.

Conclusions:

• The proposed framework effectively maps imprinted quantitative trait loci (iQTLs) in survival data.
• Genomic imprinting plays a significant role in the genetic control of hyperoxic acute lung injury (HALI) survival.
• The findings highlight the importance of considering imprinting in genetic studies of complex diseases and survival.