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Consanguinity and the sib-pair method: an approach using identity by descent between and within individuals
1Unité de recherche d'Epidémiologie Génétique, INSERM U155, Paris.
American Journal of Human Genetics
|November 1, 1996
Summary
This study extends sib-pair linkage analysis to consanguineous populations, improving detection of disease-susceptibility loci. The new chi-squared test offers greater power, especially for complex multifactorial diseases.
Area of Science:
- Genetics
- Biostatistics
- Population Genetics
Background:
- Linkage analysis in related individuals, like sibs, uses marker allele identity.
- Identity by descent (IBD) of alleles in affected inbred individuals provides linkage information for recessive diseases.
Purpose of the Study:
- To extend the sib-pair linkage analysis method to consanguineous populations.
- To develop a new linkage test utilizing condensed identity coefficients for enhanced information from IBD patterns and allelic identity within sib pairs.
- To evaluate the performance of the new test against the classical chi-squared test.
Main Methods:
- Extension of the sib-pair method to consanguineous populations using condensed identity coefficients.
- Development of a novel chi-squared test for linkage analysis.
- Comparison of the proposed test with the classical chi-squared test based on IBD sharing distributions.
- Analysis of inbreeding's impact on expected IBD sharing proportions in sib pairs.
Main Results:
- The proposed chi-squared test demonstrates superior power in detecting disease-susceptibility (DS) loci for sib pairs from first-cousin matings.
- The new test is particularly effective for models with common and incompletely penetrant DS alleles, relevant to multifactorial diseases.
- Ignoring inbreeding in linkage analysis when it exists inflates Type I error rates.
Conclusions:
- The extended sib-pair method and new chi-squared test enhance linkage detection in consanguineous populations.
- The proposed method is more powerful than the classical approach, especially for complex genetic disease models.
- Accurate accounting for inbreeding is crucial to avoid increased false positive rates in linkage tests.