Statistical Modelling 5 (2005), 119143
Graphical chain models for the analysis of complex genetic diseases:
an application to hypertension
C. Di Serio
Università Vita-Salute San Raffaele,
Via Olgettina 58,
I20132   Milan
Italy
eMail:
diserio.clelia@hsr.it
P. Vicard
Università Roma Tre,
Rome
Italy
Abstract:
A crucial task in modern genetic medicine is the understanding of
complex genetic diseases. The main complicating features are that a
combination of genetic and environmental risk factors is involved,
and the phenotype of interest may be complex. Traditional statistical
techniques based on lod-scores fail when the disease is no longer
monogenic and the underlying disease transmission model is not
defined. Different kinds of association tests have been proved to be
an appropriate and powerful statistical tool to detect a 'candidate
gene' for a complex disorder. However, statistical techniques able to
investigate direct and indirect influences among phenotypes, genotypes
and environmental risk factors, are required to analyse the association
structure of complex diseases. In this paper, we propose graphical
models as a natural tool to analyse the multifactorial structure of
complex genetic diseases. An application of this model to primary
hypertension data set is illustrated.
Keywords:
COMPLEX DISORDERS; CONDITIONAL INDEPENDENCE; GENOTYPE; GRAPHICAL CHAIN
MODELS; PHENOTYPE
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