Use of closely related affected individuals for the genetic study of complex diseases in founder populations.
We propose a method, the maximum identity length contrast (MILC) statistic, to locate genetic risk factors for complex diseases in founder populations. The MILC approach compares the identity length of parental haplotypes that are transmitted to affected offspring with the identity length of those that are not transmitted to affected offspring. Initially, the statistical properties of the method were assessed using randomly selected affected individuals with unknown relationship. Because both nuclear families with multiple affected sibs and large pedigrees are often available in founder populations, we performed simulations to investigate the properties of the MILC statistic in the presence of closely related affected individuals. The simulation showed that the use of closely related affected individuals greatly enhances the power of the statistic. For a given sample size and type I error, the use of affected sib pairs, instead of affected individuals randomly selected from the population, could increase the power by a factor of two. This increase was related to an increase of kinship-coefficient contrast between haplotype groups when closely related individuals were considered. The MILC approach allows the simultaneous use of affected individuals from a founder population and affected individuals with any kind of relationship, close or remote. We used the MILC approach to analyze the role of HLA in celiac disease and showed that the effect of HLA may be detected with the MILC approach by typing only 11 affected individuals, who were part of a single large Finnish pedigree.
Bourgain
C
C
Unité de Recherche d'Epidémiologie Génétique, INSERM U535, 94276 Le Kremlin-Bicêtre Cedex France. bourgain@kb.inserm.fr
Génin
E
E
Holopainen
P
P
Mustalahti
K
K
Mäki
M
M
Partanen
J
J
Clerget-Darpoux
F
F
D002446:Celiac Disease / Q000235:genetics*; D002874:Chromosome Mapping / Q000379:methods* / Q000706:statistics & numerical data*; D003198:Computer Simulation; D005260:Female; D005387:Finland; D018703:Founder Effect; D005787:Gene Frequency / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics; D006680:HLA Antigens / Q000235:genetics; D006239:Haplotypes / Q000235:genetics; D006801:Humans; D008297:Male; D016555:Matched-Pair Analysis; D018895:Microsatellite Repeats / Q000235:genetics; D009679:Nuclear Family; D010375:Pedigree; D012107:Research Design; D018401:Sample Size
D006680:HLA Antigens