Literature DB >> 9593115

Analytic strategies to detect linkage to a common disorder with genetically determined age of onset: diabetes mellitus in Pima Indians.

R L Hanson1, W C Knowler.   

Abstract

Segregation analysis suggests that the high prevalence of non-insulin-dependent diabetes mellitus in Pima Indians may be partially due to a single locus with a major effect on age of onset. A simulation study was conducted to evaluate the power of various age-adjustment strategies in linkage analysis to detect this putative gene in 1,862 sib-pairs from 264 potentially informative nuclear families. Simulations were performed at a recombination fraction (theta) of 0.05 for values of polymorphism information content (PIC) ranging from 0.38 to 1.00. Under the codominant age-of-onset model supported by segregation analysis, power to detect linkage (at P < 0.0001) at PIC = 1.00 was 75% for the Haseman-Elston (HE) sib-pair test and 63% for the affected sib-pair test (ASP) with no age adjustment. Substantial improvements in power were possible for the HE test by defining the trait as a survival analysis "residual" (power = 91%) and for the ASP test by use of an age-of-onset threshold above which individuals are not included in the analysis (power = 90%, for age of onset < 45 yrs). The parametric method of linkage analysis was most powerful, as long as both the analysis model and the simulation model involved a genetic effect on age of onset, regardless of whether dominance at the trait locus was misspecified. Methods of age adjustment based on the probability of eventually becoming affected only improved power when the genetic effect was on susceptibility rather than age of onset. The method of age adjustment in linkage analysis may depend on whether one anticipates a genetic effect primarily on age of onset or on ultimate susceptibility.

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Year:  1998        PMID: 9593115     DOI: 10.1002/(SICI)1098-2272(1998)15:3<299::AID-GEPI7>3.0.CO;2-#

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  7 in total

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  7 in total

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