Mh. Dizier et al., INTERACTIVE EFFECT OF 2 CANDIDATE GENES IN A DISEASE - EXTENSION OF THE MARKER-ASSOCIATION-SEGREGATION CHI(2)-METHOD, American journal of human genetics, 55(5), 1994, pp. 1042-1049
For elucidating the genetic component of multifactorial diseases, it i
s important to investigate the effect of several factors and the possi
ble interaction between them. In particular, for many diseases it is i
nteresting to study the interactive effect of two genes. In this conte
xt, the marker-association-segregation chi(2) method (MASC), initially
proposed to detect the involvement of a candidate gene in multifactor
ial diseases, is developed here to investigate the involvement of two
candidate genes and to model the joint effect of these two genes. In p
articular, it is possible to precisely determine whether the joint eff
ect of both genes is multiplicative. This extension simultaneously use
s information on two markers, one for each candidate gene, at both the
population and the familial segregation level. We show here that ther
e can be an important gain of power to detect the effect of a second g
ene in a disease when information is used simultaneously on two marker
s instead of studying each marker separately. This extension of MASC i
s then applied on a sample of insulin-dependent diabetes (IDD) familie
s typed for the markers of two candidate regions: HLA and that of the
insulin gene (INS). This analysis allows us to confirm the involvement
of INS in IDD, and the best-fitting model is a multiplicative (nonint
eractive) effect of HLA and INS, with a biallelic locus for INS and a
complementation model for HLA.