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Evidence for a novel late-onset Alzheimer disease locus on chromosome 19p13.2.


ABSTRACT: Late-onset familial Alzheimer disease (LOFAD) is a genetically heterogeneous and complex disease for which only one locus, APOE, has been definitively identified. Difficulties in identifying additional loci are likely to stem from inadequate linkage analysis methods. Nonparametric methods suffer from low power because of limited use of the data, and traditional parametric methods suffer from limitations in the complexity of the genetic model that can be feasibly used in analysis. Alternative methods that have recently been developed include Bayesian Markov chain-Monte Carlo methods. These methods allow multipoint linkage analysis under oligogenic trait models in pedigrees of arbitrary size; at the same time, they allow for inclusion of covariates in the analysis. We applied this approach to an analysis of LOFAD on five chromosomes with previous reports of linkage. We identified strong evidence of a second LOFAD gene on chromosome 19p13.2, which is distinct from APOE on 19q. We also obtained weak evidence of linkage to chromosome 10 at the same location as a previous report of linkage but found no evidence for linkage of LOFAD age-at-onset loci to chromosomes 9, 12, or 21.

SUBMITTER: Wijsman EM 

PROVIDER: S-EPMC1182019 | biostudies-literature | 2004 Sep

REPOSITORIES: biostudies-literature

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Evidence for a novel late-onset Alzheimer disease locus on chromosome 19p13.2.

Wijsman Ellen M EM   Daw E Warwick EW   Yu Change-En CE   Payami Haydeh H   Steinbart Ellen J EJ   Nochlin David D   Conlon Erin M EM   Bird Thomas D TD   Schellenberg Gerard D GD  

American journal of human genetics 20040708 3


Late-onset familial Alzheimer disease (LOFAD) is a genetically heterogeneous and complex disease for which only one locus, APOE, has been definitively identified. Difficulties in identifying additional loci are likely to stem from inadequate linkage analysis methods. Nonparametric methods suffer from low power because of limited use of the data, and traditional parametric methods suffer from limitations in the complexity of the genetic model that can be feasibly used in analysis. Alternative met  ...[more]

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