Genetic analysis of age-at-onset for cardiovascular risk factors in a brazilian family study

Suely Ruiz Giolo, Alexandre Costa Pereira, Mariza De Andrade, Camila MacIel De Oliveira, José Eduardo Krieger, Júlia Maria Pavan Soler

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Background/Aims: Statistical analysis of age-at-onset involving family data is particularly complicated because there is a correlation pattern that needs to be modeled and also because there are measurements that are censored. In this paper, our main purpose was to evaluate the effect of genetic and shared family environmental factors on age-at-onset of three cardiovascular risk factors: hypertension, diabetes and high cholesterol. Methods: The mixed-effects Cox model proposed by Pankratz et al. [2005] was used to analyze the data from 81 families, involving 1,675 individuals from the village of Baependi, in the state of Minas Gerais, Brazil. Results: The analyses performed showed that the polygenic effect plays a greater role than the shared family environmental effect in explaining the variability of the age-at-onset of hypertension, diabetes and high cholesterol. The model which simultaneously evaluated both effects indicated that there are individuals which may have risk of hypertension due to polygenic effects 130% higher than the overall average risk for the entire sample. For diabetes and high cholesterol the risks of some individuals were 115 and 45%, respectively, higher than the overall average risk for the entire population. Conclusions: Results showed evidence of significant polygenic effects indicating that age-at-onset is a useful trait for gene mapping of the common complex diseases analyzed. In addition, we found that the polygenic random component might absorb the effects of some covariates usually considered in the risk evaluation, such as gender, age and BMI.

Original languageEnglish (US)
Pages (from-to)131-138
Number of pages8
JournalHuman Heredity
Volume68
Issue number2
DOIs
StatePublished - May 2009

Keywords

  • Censored trait
  • Complex disease
  • Genetic models
  • Survival analysis

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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