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Titolo:
Incorporation of covariates in multipoint model-free linkage analysis of binary traits: how important are unaffecteds?
Autore:
Alcais, A; Abel, L;
Indirizzi:
INSERM, U550, Necker Med Sch, Lab Human Genet Infect Dis, F-75015 Paris, France INSERM Paris France F-75015 uman Genet Infect Dis, F-75015 Paris, France
Titolo Testata:
EUROPEAN JOURNAL OF HUMAN GENETICS
fascicolo: 8, volume: 9, anno: 2001,
pagine: 613 - 620
SICI:
1018-4813(200108)9:8<613:IOCIMM>2.0.ZU;2-N
Fonte:
ISI
Lingua:
ENG
Soggetto:
SIB-PAIR ANALYSIS; QUANTITATIVE TRAITS; ALCOHOL DEPENDENCE; GENETIC-LINKAGE; SIBSHIPS; SUSCEPTIBILITY; SEGREGATION; ROBUSTNESS; LOCI;
Keywords:
covariates; unaffected; linkage analysis; Maximum-Likelihood-Binomial; logistic residuals; mixed model;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
32
Recensione:
Indirizzi per estratti:
Indirizzo: Alcais, A INSERM, U550, Necker Med Sch, Lab Human Genet Infect Dis, F-75015 Paris, France INSERM Paris France F-75015 Infect Dis, F-75015 Paris, France
Citazione:
A. Alcais e L. Abel, "Incorporation of covariates in multipoint model-free linkage analysis of binary traits: how important are unaffecteds?", EUR J HUM G, 9(8), 2001, pp. 613-620

Abstract

When the mode of inheritance is unknown, genetic linkage analysis of binary trait is commonly performed using affected-sib-pair approaches. When there is evidence that some covariates influence the phenotype, incorporation of this information is expected to increase the power of the analysis since it allows (1) a better specification of the phenotype and (2) to take into account unaffected subjects. Here, we show how to account for covariates inthe sibship-oriented Maximum-Likelihood-Binomial (MLB) linkage method by means of Pearson's logistic regression residuals which are computed using phenotypic and covariate information on both affected and unaffected subjects. These residuals are subsequently analysed as a quantitative phenotype with the corresponding extension of the MLB approach which can be used withoutany assumption on the distribution of these residuals. Then, a large simulation study is performed to study the relative power of incorporating or not unaffected sibs. To this aim, two different strategies in the multipoint analysis of family data are compared: (1) using residuals of the whole sibships (ie both covariate and genotypic information on unaffecteds is needed), and (2) using affecteds only (no information on unaffecteds is needed), under different generating models according to genetic and covariate effects. The results show that there is a clear increment in the power to detect the susceptibility locus when making use of the information carried by unaffecteds, in particular for dominant mode of inheritance and when values of the covariates influencing the disease are shared by all the members of the family.

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Documento generato il 08/04/20 alle ore 11:44:42