Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.
Genet Epidemiol
; 39(4): 259-75, 2015 May.
Article
em En
| MEDLINE
| ID: mdl-25809955
ABSTRACT
In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Variação Genética
/
Marcadores Genéticos
/
Modelos Lineares
/
Locos de Características Quantitativas
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Pleiotropia Genética
/
Modelos Genéticos
Tipo de estudo:
Etiology_studies
/
Incidence_studies
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Observational_studies
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Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Genet Epidemiol
Assunto da revista:
EPIDEMIOLOGIA
/
GENETICA MEDICA
Ano de publicação:
2015
Tipo de documento:
Article
País de afiliação:
Estados Unidos