The impact of disregarding family structure on genome-wide association analysis of complex diseases in cohorts with simple pedigrees.

The impact of disregarding family structure on genome-wide association analysis of complex diseases in cohorts with simple pedigrees.
J Appl Genet. 2019 Nov 21;:
Authors: Nazarian A, Arbeev KG, Kulminski AM
Abstract
The generalized linear mixed models (GLMMs) methodology is the standard framework for genome-wide association studies (GWAS) of complex diseases in family-based cohorts. Fitting GLMMs in very large cohorts, however, can be computationally demanding. Also, the modified versions of GLMM using faster algorithms may underperform, for instance when a single nucleotide polymorphism (SNP) is correlated with fixed-effects covariates. We investigated the extent to which disregarding family structure may compromise GWAS in cohorts with simple pedigrees by contrasting logistic regression models (i.e., with no family structure) to three LMMs-based ones. Our analyses showed that the logistic regression models in general resulted in smaller P values compared with the LMMs-based models; however, the differences in P values were mostly minor. Disregarding family structure had little impact on determining disease-associated SNPs at genome-wide level of significance (i.e., P < 5E-08) as the four P values resulted from the tested methods for any SNP were all below or all above 5E-08. Nevertheless, larger discrepancies were detected between logistic regression and LMMs-based models at suggestive level of significance (i.e., of 5E-08â€...

Source: J Appl Genet - November 20, 2019 Category: Genetics & Stem Cells Authors: Nazarian A, Arbeev KG, Kulminski AM Tags: J Appl Genet Source Type: research