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Linkage Analysis

Large families with multiple affected members are extremely useful in attempts to identify risk variant(s) through linkage analyses. Briefly, sets of genotypic markers throughout the genome are used to tag particular chromosomal locations (locus; loci). If a particular marker is observed more frequently in diseased family members than in unaffected members, this suggests that the locus tagged by the marker may be involved in disease susceptibility.

Thus, linkage analysis studies the co-inheritance of disease with transmission of particular markers in affected and unaffected members of families. The greater the distance between two loci, the more likely it is that a “cross-over,” or recombination, can occur. A recombination breaks the linkage between the marker and the putative causal genomic factor. Thus, alleles (a particular form of a gene) at two close loci on a chromosome tend to be transmitted to offspring in the same combinations in which they were received from the parent, but those that are more distant may differ from parental alleles. Linkage analysis is a statistical method that compares the likelihood that an observed pattern of co-inheritance occurred because the marker and the unknown gene are truly linked (i.e., inherited together) to the likelihood that the observed data are due to chance (i.e., the marker and the unknown gene are not linked). This likelihood is expressed as a LOD (logarithm [base 10] of the odds) score. A LOD score above +3 (1,000:1 odds) is interpreted as evidence of linkage between the marker and the putative causative locus. Depending on the structure of the study sample (e.g., parents and affected offspring only; large, multiplex pedigrees) and inheritance models (e.g., autosomal dominant; no underlying model), either parametric (model specified) or nonparametric (no model specified) statistical analyses may be performed.8

 
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