A parametric model for analyzing anticipation in genetically predisposed families

Area of Science:

• Genetics
• Epidemiology
• Biostatistics

Background:

• Anticipation, a phenomenon of decreasing age-at-onset across generations, is observed in genetic diseases.
• Previous studies on anticipation are limited by focusing on affected pairs and right-truncated data.

Purpose of the Study:

• To develop and apply a statistical model for analyzing anticipation in hereditary nonpolyposis colorectal cancer (HNPCC)/Lynch syndrome.
• To account for right-censored observations and family structures in anticipation studies.

Main Methods:

• A normal random effects model was developed, incorporating covariates and handling right-censored data.
• Statistical inference was based on the likelihood function.
• The model was applied to a cohort of 824 individuals from 125 HNPCC families in the Danish HNPCC register.

Main Results:

• A significant anticipation effect was identified in HNPCC families.
• Individuals experienced a mean of 3 years earlier age-at-onset per generation.
• The model successfully corrected for incomplete observations and analyzed family data.

Conclusions:

• The developed statistical model provides a robust method for studying anticipation, especially in large cohorts with censored data.
• This approach allows for more comprehensive analyses of genetic disease progression across generations.
• Significant anticipation impacts age-at-onset in HNPCC/Lynch syndrome families.