Estimating relationships between phenotypes and subjects drawn from admixed families. Issue 7 (October 2016)

• Record Type: Journal Article
• Authors: Blue, Elizabeth; Brown, Lisa; Conomos, Matthew; Kirk, Jennifer; Nato, Alejandro; Popejoy, Alice; Raffa, Jesse; Ranola, John; Wijsman, Ellen; Thornton, Timothy
• Is Part Of: BMC proceedings. Volume 10:Issue 7(2016)
• Page Start: 357
• Page End: 362
• Publication Date: 2016-10
• Subjects: Medicine -- Congresses; Biology -- Congresses; 610.5
• DOI: 10.1186/s12919-016-0056-3
• Languages: English
• ISSNs: 1753-6561

Abstract

Abstract Background Estimating relationships among subjects in a sample, within family structures or caused by population substructure, is complicated in admixed populations. Inaccurate allele frequencies can bias both kinship estimates and tests for association between subjects and a phenotype. We analyzed the simulated and real family data from Genetic Analysis Workshop 19, and were aware of the simulation model. Results We found that kinship estimation is more accurate when marker data include common variants whose frequencies are less variable across populations. Estimates of heritability and association vary with age for longitudinally measured traits. Accounting for local ancestry identified different true associations than those identified by a traditional approach. Principal components aid kinship estimation and tests for association, but their utility is influenced by the frequency of the markers used to generate them. Conclusions Admixed families can provide a powerful resource for detecting disease loci, as well as analytical challenges. Allele frequencies, although difficult to adequately estimate in admixed populations, have a strong impact on the estimation of kinship, ancestry, and association with phenotypes. Approaches that acknowledge population structure in admixed families outperform those which ignore it.