Identifying cryptic population structure in multigenerational pedigrees in a Mexican American sample.

Area of Science:

• Population Genetics
• Genetic Epidemiology
• Statistical Genetics

Background:

• Cryptic population structure can introduce bias in genetic association studies, leading to increased Type I and Type II errors.
• While families are sometimes considered immune to these issues, this may not hold true for samples from admixed populations.

Purpose of the Study:

• To evaluate and visualize cryptic population structure within multigenerational families from an admixed population.
• To compare the effectiveness of three distinct approaches for identifying cryptic structure in family-based samples.

Main Methods:

• Utilized a principal component analysis (PCA) approach to assess population structure.
• Applied three methods: 1) using all family members, 2) a size-equalized pedigree weighting system, and 3) focusing on founders and "marry-ins".

Main Results:

• Demonstrated that different analytical approaches can reveal distinct patterns of cryptic genetic structure within the same family sample.
• Highlighted the potential for cryptic relatedness to impact genetic analyses even in seemingly homogeneous family groups.

Conclusions:

• The presence of cryptic population structure is a concern even within families, especially in admixed groups.
• The choice of method significantly influences the detection and interpretation of population structure in family-based genetic studies.