Genetic analysis of age-at-onset for cardiovascular risk factors in a Brazilian family study.
OBJECTIVE
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.
Genetics and Molecular Cardiology Laboratory, Heart Institute, Sao Paulo, Brazil. giolo@ufpr.br
Suely
S
Ruiz Giolo
Alexandre Costa
AC
Pereira
Mariza
M
de Andrade
Camila Maciel
CM
de Oliveira
José Eduardo
JE
Krieger
Júlia Maria Pavan
JM
Soler
D017668:Age of Onset; D001938:Brazil; D002318:Cardiovascular Diseases / Q000235:genetics*; D006801:Humans; D016016:Proportional Hazards Models; D012307:Risk Factors