A comparison of different linkage statistics in small to moderate sized pedigrees with complex diseases

BMC Research Notes

Konstantin Strauch¹  Antònia Flaquer¹ 

[1] Institute of Medical Biometry and Epidemiology, Philipps University Marburg, Marburg 35032, Germany

关键词: Rare variants;    Complex diseases;    MOD score;    LOD score;    NPL score;    Nonparametric analysis;    Parametric analysis;    Linkage;   

Others  :  1165995
DOI  :  10.1186/1756-0500-5-411

 received in 2012-06-26, accepted in 2012-07-25,  发布年份 2012

【 摘 要 】

Background

In the last years GWA studies have successfully identified common SNPs associated with complex diseases. However, most of the variants found this way account for only a small portion of the trait variance. This fact leads researchers to focus on rare-variant mapping with large scale sequencing, which can be facilitated by using linkage information. The question arises why linkage analysis often fails to identify genes when analyzing complex diseases. Using simulations we have investigated the power of parametric and nonparametric linkage statistics (KC-LOD, NPL, LOD and MOD scores), to detect the effect of genes responsible for complex diseases using different pedigree structures.

Results

As expected, a small number of pedigrees with less than three affected individuals has low power to map disease genes with modest effect. Interestingly, the power decreases when unaffected individuals are included in the analysis, irrespective of the true mode of inheritance. Furthermore, we found that the best performing statistic depends not only on the type of pedigrees but also on the true mode of inheritance.

Conclusions

When applied in a sensible way linkage is an appropriate and robust technique to map genes for complex disease. Unlike association analysis, linkage analysis is not hampered by allelic heterogeneity. So, why does linkage analysis often fail with complex diseases? Evidently, when using an insufficient number of small pedigrees, one might miss a true genetic linkage when actually a real effect exists. Furthermore, we show that the test statistic has an important effect on the power to detect linkage as well. Therefore, a linkage analysis might fail if an inadequate test statistic is employed. We provide recommendations regarding the most favorable test statistics, in terms of power, for a given mode of inheritance and type of pedigrees under study, in order to reduce the probability to miss a true linkage.

【 授权许可】

   
2012 Flaquer and Strauch; licensee BioMed Central Ltd.

【 图 表 】

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